Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
The Host and Network IO Team develops the full IO path implementation between a distributed system of server nodes, through the cluster, down to the custom RoCE network stack implemented in Cerebras' system, and over the proprietary IOs onto the WSE. As an FPGA developer on the team, you will own the in-chassis IO subsystem consisting of i) several cluster-facing RoCE v2 network interfaces via a custom implementation of the RDMA protocol; ii) a large programmable switching fabric; and iii) Serial IO communication with the Cerebras WSE via a proprietary protocol. You will interface between AI application-level IO teams, cluster architecture teams, and embedded software teams to develop solutions that optimize bandwidth and latency while minimizing congestion, pauses, pause spreading, unfairness, etc. The scope of work spans multiple generations of hardware products from improvements to presently deployed hardware, implementation of upcoming systems, and design/architecting of future next-gen architectures.
Lead full chassis-to-wafer IO architecture and design
Improve current RTL, implement next-gen FPGA design, define future IO architectures
Produce production-ready bitstreams for deployment into large clusters running customer inference services
Work with DV team to prevent bug slips and simplify debug
Optimize bandwidth/latency over FPGA datapath and all IO interfaces
Interface with board team facilitating and executing board bringup
Drive network performance debug of large AI clusters
Integrate leading edge networking technologies and protocols
Lead cross-functional technical projects spanning multiple teams and integrating diverse software and hardware components to deliver an improved network IO solution.
Foster clear and effective communication across teams and stakeholders.
5+ years industry experience generating production FPGA solutions, OR Master's/PhD in Computer or Electrical Engineering + 3 years industry experience,
Proficiency in Verilog development in Git based repo
Highly productive with FPGA placement & routing, timing closure, simulation, debug, and other FPGA tools/workflows
Network protocol familiarity (TCP, RoCE) and network debug tools such as Wireshark
Knowledge of network switch environments or willingness to learn (Arista, Juniper, etc.).
AI-augmented development environment
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n\n\n\nABOUT THE ROLE\n\n\n\nThe Host and Network IO Team develops the full IO path implementation between a distributed system of server nodes, through the cluster, down to the custom RoCE network stack implemented in Cerebras' system, and over the proprietary IOs onto the WSE. As an FPGA developer on the team, you will own the in-chassis IO subsystem consisting of i) several cluster-facing RoCE v2 network interfaces via a custom implementation of the RDMA protocol; ii) a large programmable switching fabric; and iii) Serial IO communication with the Cerebras WSE via a proprietary protocol. You will interface between AI application-level IO teams, cluster architecture teams, and embedded software teams to develop solutions that optimize bandwidth and latency while minimizing congestion, pauses, pause spreading, unfairness, etc. The scope of work spans multiple generations of hardware products from improvements to presently deployed hardware, implementation of upcoming systems, and design/architecting of future next-gen architectures.\n\n\n\n\nRESPONSIBILITIES\n\n - Lead full chassis-to-wafer IO architecture and design\n\n - Improve current RTL, implement next-gen FPGA design, define future IO architectures\n\n - Produce production-ready bitstreams for deployment into large clusters running customer inference services\n\n - Work with DV team to prevent bug slips and simplify debug\n\n - Optimize bandwidth/latency over FPGA datapath and all IO interfaces\n\n - Interface with board team facilitating and executing board bringup\n\n - Drive network performance debug of large AI clusters\n\n - Integrate leading edge networking technologies and protocols\n\n - Lead cross-functional technical projects spanning multiple teams and integrating diverse software and hardware components to deliver an improved network IO solution.\n\n - Foster clear and effective communication across teams and stakeholders.\n\n\n\n\nSKILLS & QUALIFICATIONS\n\n - 5+ years industry experience generating production FPGA solutions, OR Master's/PhD in Computer or Electrical Engineering + 3 years industry experience,\n\n - Proficiency in Verilog development in Git based repo\n\n - Highly productive with FPGA placement & routing, timing closure, simulation, debug, and other FPGA tools/workflows\n\n - Network protocol familiarity (TCP, RoCE) and network debug tools such as Wireshark\n\n - Knowledge of network switch environments or willingness to learn (Arista, Juniper, etc.).\n\n - AI-augmented development environment\n\n\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"ef15b7be-2fa3-4343-81aa-47ef65171af0","title":"Sr. Staff Software Engineer, Inference Platform ","department":"Software Engineering ","team":"Inference Service","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[{"location":"Toronto, CAN","address":{"postalAddress":{"postalCode":"M5H1Z5","addressRegion":"Ontario","streetAddress":"67 Richmond St W","addressCountry":"Canada","addressLocality":"Toronto"}}}],"publishedAt":"2026-06-19T21:24:23.681+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/ef15b7be-2fa3-4343-81aa-47ef65171af0","applyUrl":"https://jobs.ashbyhq.com/cerebras/ef15b7be-2fa3-4343-81aa-47ef65171af0/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About the Role
We're hiring a Staff Engineer to help lead, drive, and contribute to projects on our Inference Platform team. Our team primarily owns the orchestration layer that runs inference on our datacenter clusters, connecting cloud components with machine learning services. We are often the first team to face problems that haven't been solved yet, leading solutions across Kubernetes operators, service security policies, and CI/CD.
If you're interested in building the next-generation architecture of a globally distributed inference platform, we'd like to talk.
Responsibilities
Design, develop, test, and maintain production software, with responsibilities spanning testing, continuous development, observability, security, networking, debugging, and productionization.
Raise the effectiveness of senior engineers through design feedback, pairing, and clear technical standards.
Platform Direction. Help shape the technical direction for the Inference Platform, Kubernetes custom resource definitions, failure domains, service boundaries, and system evolution over time, and own the roadmap for major technical areas.
Reliability & Performance. Architect active-active systems with rapid failover, graceful degradation, and clear SLOs. Drive system-level improvements in latency, throughput, capacity efficiency, and resilience under unpredictable demand.
Execution on Critical Paths. Write and review production code in the most important parts of the platform. Make high-consequence architectural decisions within your area and set the technical bar through design reviews, code reviews, and sound engineering judgment.
Production Leadership. Lead on the hardest production issues and cross-system bottlenecks. Drive observability, incident response, capacity planning, and post-incident improvement with a high standard for operational rigor.
Technical Influence. Partner with ML, Product, Infrastructure, and Cloud teams to translate product and business requirements into scalable system designs, and drive alignment on shared technical decisions within your domain and adjacent platform surfaces.
Skills & Qualifications
8+ years of experience in software engineering, with substantial individual contributor experience building and operating large-scale distributed systems or cloud infrastructure.
Deep expertise in distributed systems architecture, ideally with Kubernetes.
Strong track record of making sound architectural decisions for highly available, latency-sensitive systems at scale.
Experience with security (certificates, TLS, mTLS).
Experience optimizing latency, throughput, and efficiency in high-QPS systems. Experience with TTFT and tail-latency reduction is a strong plus.
Strong proficiency in backend or systems languages such as Go or C++, with the expectation that you can contribute production code directly.
Experience designing observability and reliability practices, including metrics, logging, tracing, alerting, incident response, and SLO-driven operations.
Ability to influence senior engineers and cross-functional partners through technical credibility, communication, and judgment, especially within your domain and adjacent systems.
Preferred Skills & Qualifications
Experience with ML inference infrastructure, model serving systems, or GPU-accelerated workloads.
Location: Sunnyvale or Toronto preferred
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout the Role\n\nWe're hiring a Staff Engineer to help lead, drive, and contribute to projects on our Inference Platform team. Our team primarily owns the orchestration layer that runs inference on our datacenter clusters, connecting cloud components with machine learning services. We are often the first team to face problems that haven't been solved yet, leading solutions across Kubernetes operators, service security policies, and CI/CD.\n\nIf you're interested in building the next-generation architecture of a globally distributed inference platform, we'd like to talk.\n\nResponsibilities\n\n - Design, develop, test, and maintain production software, with responsibilities spanning testing, continuous development, observability, security, networking, debugging, and productionization.\n\n - Raise the effectiveness of senior engineers through design feedback, pairing, and clear technical standards.\n\n - Platform Direction. Help shape the technical direction for the Inference Platform, Kubernetes custom resource definitions, failure domains, service boundaries, and system evolution over time, and own the roadmap for major technical areas.\n\n - Reliability & Performance. Architect active-active systems with rapid failover, graceful degradation, and clear SLOs. Drive system-level improvements in latency, throughput, capacity efficiency, and resilience under unpredictable demand.\n\n - Execution on Critical Paths. Write and review production code in the most important parts of the platform. Make high-consequence architectural decisions within your area and set the technical bar through design reviews, code reviews, and sound engineering judgment.\n\n - Production Leadership. Lead on the hardest production issues and cross-system bottlenecks. Drive observability, incident response, capacity planning, and post-incident improvement with a high standard for operational rigor.\n\n - Technical Influence. Partner with ML, Product, Infrastructure, and Cloud teams to translate product and business requirements into scalable system designs, and drive alignment on shared technical decisions within your domain and adjacent platform surfaces.\n\nSkills & Qualifications\n\n - 8+ years of experience in software engineering, with substantial individual contributor experience building and operating large-scale distributed systems or cloud infrastructure.\n\n - Deep expertise in distributed systems architecture, ideally with Kubernetes.\n\n - Strong track record of making sound architectural decisions for highly available, latency-sensitive systems at scale.\n\n - Experience with security (certificates, TLS, mTLS).\n\n - Experience optimizing latency, throughput, and efficiency in high-QPS systems. Experience with TTFT and tail-latency reduction is a strong plus.\n\n - Strong proficiency in backend or systems languages such as Go or C++, with the expectation that you can contribute production code directly.\n\n - Experience designing observability and reliability practices, including metrics, logging, tracing, alerting, incident response, and SLO-driven operations.\n\n - Ability to influence senior engineers and cross-functional partners through technical credibility, communication, and judgment, especially within your domain and adjacent systems.\n\n - Preferred Skills & Qualifications\n\n - Experience with ML inference infrastructure, model serving systems, or GPU-accelerated workloads.\n\nLocation: Sunnyvale or Toronto preferred\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"5f0910ab-d750-4dd4-af43-21446237b45c","title":"Staff Software Engineer, Inference Cloud ","department":"Software Engineering ","team":"Inference Service","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2024-07-12T03:15:09.670+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/5f0910ab-d750-4dd4-af43-21446237b45c","applyUrl":"https://jobs.ashbyhq.com/cerebras/5f0910ab-d750-4dd4-af43-21446237b45c/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About the Role
We're hiring a Staff Engineer to own major areas of the architecture of our Inference Cloud Platform. This team owns the cloud layer behind our Inference Service, with responsibility for availability, latency, reliability, and global scale.
This is a hands-on individual contributor role for an engineer who wants to work on the hardest distributed systems problems in the stack: multi-region traffic architecture, graceful degradation under bursty AI workloads, performance at high QPS, and the operating model for a platform that has to stay fast and available under load. You'll write code, lead key architectural decisions in your domain, debug production issues, and help shape technical direction across adjacent teams.
If you're interested in building the next-generation architecture of a globally distributed inference platform, we'd like to talk.
Responsibilities
Platform Direction. Help shape the technical direction for the Inference Cloud Platform, including multi-region topology, failure domains, service boundaries, and system evolution over time, and own the roadmap for major technical areas.
Core Cloud Systems. Design and build critical platform components such as service discovery, request routing, load balancing, caching, batching, and traffic management for AI inference workloads.
Reliability & Performance. Architect active-active systems with rapid failover, graceful degradation, and clear SLOs. Drive system-level improvements in latency, throughput, capacity efficiency, and resilience under unpredictable demand.
Traffic Control & Service Tiers. Define platform mechanisms for admission control, quota management, rate limiting, and differentiated quality of service across workload types and customer tiers.
Execution on Critical Paths. Write and review production code in the most important parts of the platform. Make high-consequence architectural decisions within your area and set the technical bar through design reviews, code reviews, and sound engineering judgment.
Production Leadership. Lead on the hardest production issues and cross-system bottlenecks. Drive observability, incident response, capacity planning, and post-incident improvement with a high standard for operational rigor.
Technical Influence. Partner with ML, Product, Infrastructure, and Platform teams to translate product and business requirements into scalable system designs, and drive alignment on shared technical decisions within your domain and adjacent platform surfaces.
Mentorship. Raise the effectiveness of senior engineers through design feedback, pairing, and clear technical standards.
Skills & Qualifications
8+ years of experience in software engineering, with substantial individual contributor experience building and operating large-scale distributed systems or cloud infrastructure.
Deep expertise in distributed systems architecture in cloud environments, including networking, compute orchestration, container platforms, and multi-region production services.
Strong track record of making sound architectural decisions for highly available, latency-sensitive systems at scale.
Experience optimizing latency, throughput, and efficiency in high-QPS systems. Experience with TTFT and tail-latency reduction is a strong plus.
Strong proficiency in backend or systems languages such as Go, C++, or Python, with the expectation that you can contribute production code directly.
Experience designing observability and reliability practices, including metrics, logging, tracing, alerting, incident response, and SLO-driven operations.
Ability to influence senior engineers and cross-functional partners through technical credibility, communication, and judgment, especially within your domain and adjacent systems.
Preferred Skills & Qualifications
Experience with ML inference infrastructure, model serving systems, or GPU-accelerated workloads.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout the Role\n\nWe're hiring a Staff Engineer to own major areas of the architecture of our Inference Cloud Platform. This team owns the cloud layer behind our Inference Service, with responsibility for availability, latency, reliability, and global scale.\n\nThis is a hands-on individual contributor role for an engineer who wants to work on the hardest distributed systems problems in the stack: multi-region traffic architecture, graceful degradation under bursty AI workloads, performance at high QPS, and the operating model for a platform that has to stay fast and available under load. You'll write code, lead key architectural decisions in your domain, debug production issues, and help shape technical direction across adjacent teams.\n\nIf you're interested in building the next-generation architecture of a globally distributed inference platform, we'd like to talk.\n\nResponsibilities\n\n - Platform Direction. Help shape the technical direction for the Inference Cloud Platform, including multi-region topology, failure domains, service boundaries, and system evolution over time, and own the roadmap for major technical areas.\n\n - Core Cloud Systems. Design and build critical platform components such as service discovery, request routing, load balancing, caching, batching, and traffic management for AI inference workloads.\n\n - Reliability & Performance. Architect active-active systems with rapid failover, graceful degradation, and clear SLOs. Drive system-level improvements in latency, throughput, capacity efficiency, and resilience under unpredictable demand.\n\n - Traffic Control & Service Tiers. Define platform mechanisms for admission control, quota management, rate limiting, and differentiated quality of service across workload types and customer tiers.\n\n - Execution on Critical Paths. Write and review production code in the most important parts of the platform. Make high-consequence architectural decisions within your area and set the technical bar through design reviews, code reviews, and sound engineering judgment.\n\n - Production Leadership. Lead on the hardest production issues and cross-system bottlenecks. Drive observability, incident response, capacity planning, and post-incident improvement with a high standard for operational rigor.\n\n - Technical Influence. Partner with ML, Product, Infrastructure, and Platform teams to translate product and business requirements into scalable system designs, and drive alignment on shared technical decisions within your domain and adjacent platform surfaces.\n\n - Mentorship. Raise the effectiveness of senior engineers through design feedback, pairing, and clear technical standards.\n\nSkills & Qualifications\n\n - 8+ years of experience in software engineering, with substantial individual contributor experience building and operating large-scale distributed systems or cloud infrastructure.\n\n - Deep expertise in distributed systems architecture in cloud environments, including networking, compute orchestration, container platforms, and multi-region production services.\n\n - Strong track record of making sound architectural decisions for highly available, latency-sensitive systems at scale.\n\n - Experience optimizing latency, throughput, and efficiency in high-QPS systems. Experience with TTFT and tail-latency reduction is a strong plus.\n\n - Strong proficiency in backend or systems languages such as Go, C++, or Python, with the expectation that you can contribute production code directly.\n\n - Experience designing observability and reliability practices, including metrics, logging, tracing, alerting, incident response, and SLO-driven operations.\n\n - Ability to influence senior engineers and cross-functional partners through technical credibility, communication, and judgment, especially within your domain and adjacent systems.\n\nPreferred Skills & Qualifications\n\n - Experience with ML inference infrastructure, model serving systems, or GPU-accelerated workloads.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"0fbdfff1-78cc-4fac-b99a-a90b5f244cc2","title":"Distributed Systems Cluster Security Software – Engineering Lead","department":"Software Engineering ","team":"Cluster","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2025-03-24T19:36:56.049+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/0fbdfff1-78cc-4fac-b99a-a90b5f244cc2","applyUrl":"https://jobs.ashbyhq.com/cerebras/0fbdfff1-78cc-4fac-b99a-a90b5f244cc2/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
In this role, you will be the security czar for the Cerebras’s AI cluster product. Such AI clusters have 100’s of Wafer-scale accelerator systems, 1000’s of high-end servers, and several 1000’s of networking ports including switches. Plus, there will be network attached storage, all in a large-scale datacenter.
You will ensure that Cerebras’s large-scale AI clusters are secured through first-principles, best practices, security-first based engineering. Cerebras cluster involves complex HW components, networking and a vertically integrated cluster management software stack – all the way from a bare-metal deployment that brings up an operational cluster to a suite of cluster management software that enables multi-tenant higher-level training and inference services to be hosted on such large clusters.
Your role will be to ensure both end-to-end security as well as privacy of such cluster use-cases. You will develop security engineering solutions that have the necessary network access control, user access controls, and world-class multi-tenancy solution
Responsibilities
Be the primary engineering face and owner of cluster security.
Provide strong technical leadership in cluster security for the company.
Actively work with corporate security, and customers to identify and define security enhancements needed.
Build engineering driven software that will provide guardrails, detection solution and response tools for vulnerabilities at all layers of vertical stack (includes HW and SW).
Straddle vertically and horizontally cross functional collaboration to ensure end-to-end cluster software is secure.
Develop, maintain and execute roadmap of the cluster security product.
Build an outstanding engineering team to deliver world-class security solution.
Skills & Qualifications
3+ years of demonstrated engineering leadership/management role in distributed systems security.
Proven track record of delivering product, launching and deploying secured distributed solutions to customers.
Excellent communication, articulation, collaboration and ability to act as a stakeholder.
Tough decision-making skills with data and trade-off analysis.
Outstanding sense for product and user journeys, out-of-box thinker.
Outstanding road map and schedule execution skills under tight timeline and budgets.
Strong background in multi-tenancy of large scale clusters is necessary.
Strong technical experience in computer and cluster networks is necessary.
Strong technical background in distributed systems software development (K8s and its ecosystem) is preferred.
Technical experience with bare metal cluster management software and related monitoring is preferred.
The salary range for this position is $140,000 - $240,000 annually. Actual compensation will be determined based on factors such as experience, skills, qualifications, and location.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nIn this role, you will be the security czar for the Cerebras’s AI cluster product. Such AI clusters have 100’s of Wafer-scale accelerator systems, 1000’s of high-end servers, and several 1000’s of networking ports including switches. Plus, there will be network attached storage, all in a large-scale datacenter.\n\nYou will ensure that Cerebras’s large-scale AI clusters are secured through first-principles, best practices, security-first based engineering. Cerebras cluster involves complex HW components, networking and a vertically integrated cluster management software stack – all the way from a bare-metal deployment that brings up an operational cluster to a suite of cluster management software that enables multi-tenant higher-level training and inference services to be hosted on such large clusters.\n\nYour role will be to ensure both end-to-end security as well as privacy of such cluster use-cases. You will develop security engineering solutions that have the necessary network access control, user access controls, and world-class multi-tenancy solution\n\nResponsibilities\n\n - Be the primary engineering face and owner of cluster security.\n\n - Provide strong technical leadership in cluster security for the company.\n\n - Actively work with corporate security, and customers to identify and define security enhancements needed.\n\n - Build engineering driven software that will provide guardrails, detection solution and response tools for vulnerabilities at all layers of vertical stack (includes HW and SW).\n\n - Straddle vertically and horizontally cross functional collaboration to ensure end-to-end cluster software is secure.\n\n - Develop, maintain and execute roadmap of the cluster security product.\n\n - Build an outstanding engineering team to deliver world-class security solution.\n\nSkills & Qualifications\n\n - 3+ years of demonstrated engineering leadership/management role in distributed systems security.\n\n - Proven track record of delivering product, launching and deploying secured distributed solutions to customers.\n\n - Excellent communication, articulation, collaboration and ability to act as a stakeholder.\n\n - Tough decision-making skills with data and trade-off analysis.\n\n - Outstanding sense for product and user journeys, out-of-box thinker.\n\n - Outstanding road map and schedule execution skills under tight timeline and budgets.\n\n - Strong background in multi-tenancy of large scale clusters is necessary.\n\n - Strong technical experience in computer and cluster networks is necessary.\n\n - Strong technical background in distributed systems software development (K8s and its ecosystem) is preferred.\n\n - Technical experience with bare metal cluster management software and related monitoring is preferred.\n\nThe salary range for this position is $140,000 - $240,000 annually. Actual compensation will be determined based on factors such as experience, skills, qualifications, and location.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"5985b733-1290-4603-8e66-f91c677e99ee","title":"AI Silicon Physical Design Engineer","department":"Hardware","team":"Silicon","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2025-04-21T22:48:23.991+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/5985b733-1290-4603-8e66-f91c677e99ee","applyUrl":"https://jobs.ashbyhq.com/cerebras/5985b733-1290-4603-8e66-f91c677e99ee/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
Join our close-knit physical design team where you'll excel in synthesizing, placing, and routing high speed designs. Experience the full spectrum of physical design and implementation, collaborating closely with the RTL team and integrating these blocks seamlessly into the full-chip architecture.
Skills & Qualifications:
10+ years of physical design & physical verification experience.
Strong knowledge of block level and full-chip physical verification methodology.
Strong experience in block/subsystem timing closure.
Expert at optimizing for the best power/performance and area.
Experience with the complete physical design flow.
Expert with ICV or Calibre tools resolving block and full-chip DRC and LVS issues.
Expert with IR/EM analysis and resolution.
Strong background in STA, constraint drafting and timing convergence at block, partition and fullchip.
Should demonstrate and raise the bar for “ownership”, “deep dive” and should demonstrate strong fundamental understanding of PD concepts.
Good understanding of full chip floor planning and integration.
Strong ability in scripting languages like Tcl and Python. Ability to make flow enhancements.
Demonstrated ability to work with RTL teams to optimize for physical design.
Skills in Design Compiler, Fusion Compiler, ICC2 or similar physical design tools.
BS or MS in Electrical Engineering.
Preferred:
Knowledge of CPU/GPU design a plus.
Block/partition PD, PDV, IR would be good to have.
Knowledge of Synopsys tool suite is a plus.
The salary range for this position is $150,000 – $250,000 annually. Actual compensation will be determined based on factors such as experience, skills, qualifications, and location.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nJoin our close-knit physical design team where you'll excel in synthesizing, placing, and routing high speed designs. Experience the full spectrum of physical design and implementation, collaborating closely with the RTL team and integrating these blocks seamlessly into the full-chip architecture.\n\n\n\nSkills & Qualifications:\n\n - 10+ years of physical design & physical verification experience.\n\n - Strong knowledge of block level and full-chip physical verification methodology.\n\n - Strong experience in block/subsystem timing closure.\n\n - Expert at optimizing for the best power/performance and area.\n\n - Experience with the complete physical design flow.\n\n - Expert with ICV or Calibre tools resolving block and full-chip DRC and LVS issues.\n\n - Expert with IR/EM analysis and resolution.\n\n - Strong background in STA, constraint drafting and timing convergence at block, partition and fullchip.\n\n - Should demonstrate and raise the bar for “ownership”, “deep dive” and should demonstrate strong fundamental understanding of PD concepts.\n\n - Good understanding of full chip floor planning and integration.\n\n - Strong ability in scripting languages like Tcl and Python. Ability to make flow enhancements.\n\n - Demonstrated ability to work with RTL teams to optimize for physical design.\n\n - Skills in Design Compiler, Fusion Compiler, ICC2 or similar physical design tools.\n\n - BS or MS in Electrical Engineering.\n\n\n\nPreferred:\n\n - Knowledge of CPU/GPU design a plus.\n\n - Block/partition PD, PDV, IR would be good to have.\n\n - Knowledge of Synopsys tool suite is a plus.\n \n \n\nThe salary range for this position is $150,000 – $250,000 annually. Actual compensation will be determined based on factors such as experience, skills, qualifications, and location.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"c3890fd4-99de-4a22-b442-b6a77a717dfb","title":"Full Stack LLM Engineer","department":"Software Engineering ","team":"Inference Core","employmentType":"FullTime","location":"Toronto, CAN","secondaryLocations":[],"publishedAt":"2025-07-18T20:38:09.402+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"postalCode":"M5H1Z5","addressRegion":"Ontario","streetAddress":"67 Richmond St W","addressCountry":"Canada","addressLocality":"Toronto"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/c3890fd4-99de-4a22-b442-b6a77a717dfb","applyUrl":"https://jobs.ashbyhq.com/cerebras/c3890fd4-99de-4a22-b442-b6a77a717dfb/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About the Role
We are seeking a versatile and experienced engineer to join our Inference Core Model Bringup team. This team is responsible to rapidly bring up state-of-the-art open-source models (like LLaMA, Qwen, etc) or customer-provided proprietary models on our Cerebras CSX systems. Success in this role requires a system-minded generalist who thrives in fast-paced bringup environments and is comfortable working across the entire Cerebras software stack.
Your work will play a critical role in achieving unprecedented levels of performance, efficiency, and scalability for AI applications.
Responsibilities
Contribute to the end-to-end bring up of ML models on Cerebras CSX systems.
Work across the stack: model architecture translation, graph lowering, compiler optimizations, runtime integration, and performance tuning.
Debug performance and correctness issues spanning model code, compiler IRs, runtime behavior, and hardware utilization.
Propose and prototype improvements across tools, APIs, or automation flows to accelerate future bring ups.
Skills & Qualifications
Bachelor’s, Master’s, or PhD in Computer Science, Engineering, or a related field.
Comfort navigating the full AI toolchain: Python modeling code, compiler IRs, performance profiling, etc.
Strong debugging skills across performance, numerical accuracy, and runtime integration.
Experience with deep learning frameworks (e.g., PyTorch, TensorFlow) and familiarity with model internals (e.g., attention, MoE, diffusion).
Proficiency in C/C++ programming and experience with low-level optimization.
Proven experience in compiler development, particularly with LLVM and/or MLIR.
Strong background in optimization techniques, particularly those involving NP-hard problems.
What We Offer
Competitive salary and benefits package.
Opportunities for professional growth and career advancement.
A dynamic and innovative work environment.
The chance to work on cutting-edge technologies and make a significant impact on the future of AI.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout the Role\nWe are seeking a versatile and experienced engineer to join our Inference Core Model Bringup team. This team is responsible to rapidly bring up state-of-the-art open-source models (like LLaMA, Qwen, etc) or customer-provided proprietary models on our Cerebras CSX systems. Success in this role requires a system-minded generalist who thrives in fast-paced bringup environments and is comfortable working across the entire Cerebras software stack.\nYour work will play a critical role in achieving unprecedented levels of performance, efficiency, and scalability for AI applications.\n\nResponsibilities\n\n - Contribute to the end-to-end bring up of ML models on Cerebras CSX systems.\n\n - Work across the stack: model architecture translation, graph lowering, compiler optimizations, runtime integration, and performance tuning.\n\n - Debug performance and correctness issues spanning model code, compiler IRs, runtime behavior, and hardware utilization.\n\n - Propose and prototype improvements across tools, APIs, or automation flows to accelerate future bring ups.\n\nSkills & Qualifications\n\n - Bachelor’s, Master’s, or PhD in Computer Science, Engineering, or a related field.\n\n - Comfort navigating the full AI toolchain: Python modeling code, compiler IRs, performance profiling, etc.\n\n - Strong debugging skills across performance, numerical accuracy, and runtime integration.\n\n - Experience with deep learning frameworks (e.g., PyTorch, TensorFlow) and familiarity with model internals (e.g., attention, MoE, diffusion).\n\n - Proficiency in C/C++ programming and experience with low-level optimization.\n\n - Proven experience in compiler development, particularly with LLVM and/or MLIR.\n\n - Strong background in optimization techniques, particularly those involving NP-hard problems.\n\nWhat We Offer\n\n - Competitive salary and benefits package.\n\n - Opportunities for professional growth and career advancement.\n\n - A dynamic and innovative work environment.\n\n - The chance to work on cutting-edge technologies and make a significant impact on the future of AI.\n\n \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"2484eb99-2bbf-45df-a3c5-bdd337584726","title":"Principal Engineer, Inference Cloud ","department":"Software Engineering ","team":"Inference Service","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2025-09-29T12:43:55.551+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/2484eb99-2bbf-45df-a3c5-bdd337584726","applyUrl":"https://jobs.ashbyhq.com/cerebras/2484eb99-2bbf-45df-a3c5-bdd337584726/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
We're hiring a Principal Engineer for our Inference Cloud Platform. This team owns the cloud layer behind our Inference Service, including availability, latency, reliability, and multi-region scale.
This is one of the most senior IC roles on the team, for someone who can identify the highest-leverage platform problems, set direction across multiple teams, define long-term architecture, and write production code on critical paths.
Many of the key decisions are ambiguous at the outset; you’ll need to frame the problem, make tradeoffs, and drive execution without a clear spec.
The scope includes multi-region traffic architecture, graceful degradation under bursty AI workloads, high-QPS performance, and the operating model for a platform that needs to remain fast and available under changing demand. You'll partner closely with ML, Product and Infrastructure teams.
Responsibilities
Problem Definition & Prioritization. Identify the most important technical problems for the platform, often before there's a clear ask. Make explicit tradeoff decisions about what the platform will and won't support, with reasoning that holds up under scrutiny from senior engineering leadership.
Platform Direction. Set the long-term technical direction for the Inference Cloud Platform, including multi-region topology, failure domains, service boundaries, and system evolution over time.
Reliability & Performance. Architect active-active systems with rapid failover and graceful degradation (circuit breaking, backpressure, load shedding) with clear SLOs. Drive improvements in latency, throughput, capacity efficiency, and resilience under unpredictable demand.
Code & Design Reviews. Contribute production code in critical paths, review designs and implementations, and make architectural decisions including build-vs-buy tradeoffs with long-term operational consequences.
Production Leadership. Lead on the hardest production issues and cross-system bottlenecks. Drive observability, incident response, capacity planning, and post-incident improvement with a high standard for operational rigor.
Technical Strategy Beyond Your Team. Drive platform-wide decisions across adjacent teams on reliability, API design, capacity planning, and deployment strategy through strong technical judgment. Translate product and business requirements into scalable system designs and drive alignment on shared infrastructure decisions.
Mentorship. Raise the quality of technical decision-making across teams through design feedback, pairing, and clear engineering standards.
Skills & Qualifications
10+ years of experience in software engineering, with substantial individual contributor experience building and operating large-scale distributed systems or cloud infrastructure.
Deep expertise in distributed systems architecture in cloud environments, including networking, compute orchestration, container platforms, and multi-region production services.
Strong track record of making sound architectural decisions for highly available, latency-sensitive systems at scale, demonstrated through systems you built directly.
Experience optimizing latency, throughput, and efficiency in high-QPS systems. Experience with TTFT and tail-latency reduction is a strong plus.
Strong proficiency in backend or systems languages such as Go, C++, or Python, with the expectation that you can contribute production code directly.
Experience designing observability and reliability practices, including metrics, logging, tracing, alerting, incident response, and SLI/SLO/SLA-driven operations.
Ability to influence senior engineers, technical leads, and cross-functional partners through technical credibility, communication, and judgment.
Experience with ML inference infrastructure, model serving systems, or GPU-accelerated workloads is a plus.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nWe're hiring a Principal Engineer for our Inference Cloud Platform. This team owns the cloud layer behind our Inference Service, including availability, latency, reliability, and multi-region scale. \n\nThis is one of the most senior IC roles on the team, for someone who can identify the highest-leverage platform problems, set direction across multiple teams, define long-term architecture, and write production code on critical paths. \n\nMany of the key decisions are ambiguous at the outset; you’ll need to frame the problem, make tradeoffs, and drive execution without a clear spec. \n\nThe scope includes multi-region traffic architecture, graceful degradation under bursty AI workloads, high-QPS performance, and the operating model for a platform that needs to remain fast and available under changing demand. You'll partner closely with ML, Product and Infrastructure teams. \n\nResponsibilities \n\n - Problem Definition & Prioritization. Identify the most important technical problems for the platform, often before there's a clear ask. Make explicit tradeoff decisions about what the platform will and won't support, with reasoning that holds up under scrutiny from senior engineering leadership. \n\n - Platform Direction. Set the long-term technical direction for the Inference Cloud Platform, including multi-region topology, failure domains, service boundaries, and system evolution over time. \n\n - Reliability & Performance. Architect active-active systems with rapid failover and graceful degradation (circuit breaking, backpressure, load shedding) with clear SLOs. Drive improvements in latency, throughput, capacity efficiency, and resilience under unpredictable demand. \n\n - Code & Design Reviews. Contribute production code in critical paths, review designs and implementations, and make architectural decisions including build-vs-buy tradeoffs with long-term operational consequences. \n\n - Production Leadership. Lead on the hardest production issues and cross-system bottlenecks. Drive observability, incident response, capacity planning, and post-incident improvement with a high standard for operational rigor. \n\n - Technical Strategy Beyond Your Team. Drive platform-wide decisions across adjacent teams on reliability, API design, capacity planning, and deployment strategy through strong technical judgment. Translate product and business requirements into scalable system designs and drive alignment on shared infrastructure decisions. \n\n - Mentorship. Raise the quality of technical decision-making across teams through design feedback, pairing, and clear engineering standards. \n\nSkills & Qualifications \n\n - 10+ years of experience in software engineering, with substantial individual contributor experience building and operating large-scale distributed systems or cloud infrastructure. \n\n - Deep expertise in distributed systems architecture in cloud environments, including networking, compute orchestration, container platforms, and multi-region production services. \n\n - Strong track record of making sound architectural decisions for highly available, latency-sensitive systems at scale, demonstrated through systems you built directly. \n\n - Experience optimizing latency, throughput, and efficiency in high-QPS systems. Experience with TTFT and tail-latency reduction is a strong plus. \n\n - Strong proficiency in backend or systems languages such as Go, C++, or Python, with the expectation that you can contribute production code directly. \n\n - Experience designing observability and reliability practices, including metrics, logging, tracing, alerting, incident response, and SLI/SLO/SLA-driven operations. \n\n - Ability to influence senior engineers, technical leads, and cross-functional partners through technical credibility, communication, and judgment. \n\n - Experience with ML inference infrastructure, model serving systems, or GPU-accelerated workloads is a plus. \n\n \n\n \n\n \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"1c63f451-b4d1-44e4-a31a-8c0cd3045222","title":"Manager kernel software ","department":"Software Engineering ","team":"Voyager","employmentType":"FullTime","location":"Bengaluru, IND","secondaryLocations":[],"publishedAt":"2025-10-06T15:45:47.388+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressRegion":"Karnataka","addressCountry":"India","addressLocality":"Bengaluru"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/1c63f451-b4d1-44e4-a31a-8c0cd3045222","applyUrl":"https://jobs.ashbyhq.com/cerebras/1c63f451-b4d1-44e4-a31a-8c0cd3045222/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
As a Kernel Engineer on our team, you will develop high-performance software solutions at the intersection of hardware and software, developing high-performance software for cutting-edge AI and HPC workloads. Your focus will be on implementing, optimizing, and scaling deep learning operations to fully leverage our custom, massively parallel processor architecture.
You will be part of a world-class team responsible for the design, performance tuning, and validation of foundational ML and HPC kernels. This includes building a library of parallel and distributed algorithms that maximize compute utilization and push the boundaries of training efficiency for state-of-the-art AI models. Your work will be critical to unlocking the full potential of our hardware and accelerating the pace of AI innovation.
Responsibilities
Develop design specifications for new machine learning and linear algebra kernels and mapping to the Cerebras WSE System using various parallel programming algorithms.
Develop and debug kernel library of highly optimized low level assembly instruction and C-like domain specific language routines to implement algorithms targeting the Cerebras hardware system.
Develop and debug high-performance kernel routines in low-level assembly and a custom C-like (CSL) language, implementing algorithms optimized for the Cerebras hardware system.
Using mathematical models and analysis to measure the software performance and inform design decisions.
Develop and integrate unit and system testing methodologies to verify correct functionality and performance of kernel libraries.
Study emerging trends in Machine Learning applications and help evolve Kernel library architecture to address computational challenges of the start-of-the-art Neural Networks.
Interact with chip and system architects to optimize instruction sets, microarchitecture, and IO of next generation systems.
Skills & Qualifications
Bachelor’s, Master’s, PhD, or foreign equivalent in Computer Science, Computer Engineering, Mathematics, or a related field.
Proven experience leading technical teams, including mentoring engineers, setting technical direction, and driving execution.
Strong understanding of hardware architecture concepts and willingness to dive into new system architectures.
Proficiency in C++ and Python; experience with low-level systems programming.
Familiarity with library/API development best practices and performance optimization.
Excellent debugging skills across complex, layered software stacks.
Preferred Skills & Qualifications
Experience leading teams in kernel development, performance optimization, or low-level systems programming.
Strong background in parallel algorithms and distributed memory systems.
Hands-on experience with accelerators such as GPUs, FPGAs, or other custom hardware.
Familiarity with machine learning workloads and frameworks like TensorFlow and PyTorch.
Understanding of HPC kernels and strategies for optimizing them on modern architectures.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nAs a Kernel Engineer on our team, you will develop high-performance software solutions at the intersection of hardware and software, developing high-performance software for cutting-edge AI and HPC workloads. Your focus will be on implementing, optimizing, and scaling deep learning operations to fully leverage our custom, massively parallel processor architecture.\n\nYou will be part of a world-class team responsible for the design, performance tuning, and validation of foundational ML and HPC kernels. This includes building a library of parallel and distributed algorithms that maximize compute utilization and push the boundaries of training efficiency for state-of-the-art AI models. Your work will be critical to unlocking the full potential of our hardware and accelerating the pace of AI innovation.\n\nResponsibilities \n\n \n\n - Develop design specifications for new machine learning and linear algebra kernels and mapping to the Cerebras WSE System using various parallel programming algorithms.\n\n - Develop and debug kernel library of highly optimized low level assembly instruction and C-like domain specific language routines to implement algorithms targeting the Cerebras hardware system.\n\n - Develop and debug high-performance kernel routines in low-level assembly and a custom C-like (CSL) language, implementing algorithms optimized for the Cerebras hardware system.\n\n - Using mathematical models and analysis to measure the software performance and inform design decisions.\n\n - Develop and integrate unit and system testing methodologies to verify correct functionality and performance of kernel libraries.\n\n - Study emerging trends in Machine Learning applications and help evolve Kernel library architecture to address computational challenges of the start-of-the-art Neural Networks.\n\n - Interact with chip and system architects to optimize instruction sets, microarchitecture, and IO of next generation systems.\n\n \n\nSkills & Qualifications \n\n - Bachelor’s, Master’s, PhD, or foreign equivalent in Computer Science, Computer Engineering, Mathematics, or a related field. \n\n - Proven experience leading technical teams, including mentoring engineers, setting technical direction, and driving execution. \n\n - Strong understanding of hardware architecture concepts and willingness to dive into new system architectures. \n\n - Proficiency in C++ and Python; experience with low-level systems programming. \n\n - Familiarity with library/API development best practices and performance optimization. \n\n - Excellent debugging skills across complex, layered software stacks. \n\nPreferred Skills & Qualifications \n\n - Experience leading teams in kernel development, performance optimization, or low-level systems programming. \n\n - Strong background in parallel algorithms and distributed memory systems. \n\n - Hands-on experience with accelerators such as GPUs, FPGAs, or other custom hardware. \n\n - Familiarity with machine learning workloads and frameworks like TensorFlow and PyTorch. \n\n - Understanding of HPC kernels and strategies for optimizing them on modern architectures.\n\n \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"3c456e76-308b-4a6b-8e9a-01def6383d28","title":"Staff Site Reliability Engineer – Automation and Platform ","department":"Software Engineering ","team":"Inference Service","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[{"location":"Toronto, CAN","address":{"postalAddress":{"postalCode":"M5H1Z5","addressRegion":"Ontario","streetAddress":"67 Richmond St W","addressCountry":"Canada","addressLocality":"Toronto"}}}],"publishedAt":"2025-10-03T21:18:58.442+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/3c456e76-308b-4a6b-8e9a-01def6383d28","applyUrl":"https://jobs.ashbyhq.com/cerebras/3c456e76-308b-4a6b-8e9a-01def6383d28/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About the Role
We are building a high-performance SRE function to support one of the world’s fastest-growing AI inference services, powered by the Wafer-Scale Engine (WSE). This team will help deliver world-class, ultra-reliable inference infrastructure for leading model builders such as OpenAI and other frontier labs.
As a Staff SRE, you will lead the engineering effort to eliminate toil at scale by driving implementation of self-service delivery pipelines, shared observability common tooling. This role starts with ~1 month of hands-on operational immersion to gain deep familiarity with our current stack, production pain points, and high-stakes workflows.
From there, your primary focus shifts to architecting and delivering the \"tomorrow\" layer: declarative GitOps-driven CD for model releases, capacity provisioning and cluster upgrades. Success over the first year in this role will be defined by enabling core teams, product managers, external customers, and cluster stakeholders to operate in a fully self-service model with strong reliability guarantees.
You will partner with our early-career SRE sub-team, who own day-to-day operations. This will allow you to deeply understand their pain points, automate their toil, and mentor them as platform engineers.
You will collaborate with the tech leads and the leadership team across core, cluster, cloud, and product stakeholders. This work will shift reliability from an ops-only burden to a shared engineering discipline that underpins frontier AI inference at scale.
If you are a proven Staff+ engineer who enjoys turning complexity into elegant reliability at scale, this is your chance to lead this transformation from the front.
This role does not require 24/7 on-call rotations.
Key Responsibilities
Define and implement a robust strategy for delivering and running software reliably and at scale across multiple datacenters and cloud-based solutions.
Architect self-service platforms and internal tooling that lets product teams, external customers, and cluster operators safely trigger and observe critical workflows with minimal handoffs.
Define and evolve reliability practices for inference workloads, including SLOs and SLIs for latency, throughput, and accuracy stability; error budgets; blameless postmortems; chaos testing; and capacity forecasting across multi-datacenter and on-prem environments.
Mentor mid-level SREs, support critical incident escalations, and use production pain points to prioritize the highest-leverage automation work.
Measure and drive impact through clear metrics, including toil reduction, deployment velocity, SLO compliance, MTTR, and adoption of self-service workflows.
Required Experience & Skills
8+ years in SRE, infrastructure engineering, or platform engineering, with a strong record of improving automation and reliability at large scale in FAANG, hyperscaler, or similarly demanding environments.
Deep expertise operating large scale heterogenous clusters with a proprietary cloud control plane
Proven track record designing and delivering CI/CD or GitOps systems using Argo CD or similar tools, with strong safety and observability built in.
Hands-on experience with observability systems such as Loki, Tempo, Mimir, and Prometheus
Ability to lead complex projects end to end, influence cross-functional stakeholders, and communicate technical direction clearly.
Nice-to-Haves
Experience with Bazel or other large-scale build systems in production.
Background in AI/ML inference systems, including model serving runtimes, GPU or wafer-scale orchestration, latency and accuracy SLOs, or drift monitoring.
Prior work on predictive autoscaling, chaos engineering, or cost-aware capacity planning for compute-intensive workloads.
Location
SF Bay Area
Toronto
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout the Role\n\nWe are building a high-performance SRE function to support one of the world’s fastest-growing AI inference services, powered by the Wafer-Scale Engine (WSE). This team will help deliver world-class, ultra-reliable inference infrastructure for leading model builders such as OpenAI and other frontier labs.\n\nAs a Staff SRE, you will lead the engineering effort to eliminate toil at scale by driving implementation of self-service delivery pipelines, shared observability common tooling. This role starts with ~1 month of hands-on operational immersion to gain deep familiarity with our current stack, production pain points, and high-stakes workflows.\n\nFrom there, your primary focus shifts to architecting and delivering the \"tomorrow\" layer: declarative GitOps-driven CD for model releases, capacity provisioning and cluster upgrades. Success over the first year in this role will be defined by enabling core teams, product managers, external customers, and cluster stakeholders to operate in a fully self-service model with strong reliability guarantees.\n\nYou will partner with our early-career SRE sub-team, who own day-to-day operations. This will allow you to deeply understand their pain points, automate their toil, and mentor them as platform engineers.\n\nYou will collaborate with the tech leads and the leadership team across core, cluster, cloud, and product stakeholders. This work will shift reliability from an ops-only burden to a shared engineering discipline that underpins frontier AI inference at scale.\n\nIf you are a proven Staff+ engineer who enjoys turning complexity into elegant reliability at scale, this is your chance to lead this transformation from the front.\n\nThis role does not require 24/7 on-call rotations.\n\nKey Responsibilities\n\n - Define and implement a robust strategy for delivering and running software reliably and at scale across multiple datacenters and cloud-based solutions.\n\n - Architect self-service platforms and internal tooling that lets product teams, external customers, and cluster operators safely trigger and observe critical workflows with minimal handoffs.\n\n - Define and evolve reliability practices for inference workloads, including SLOs and SLIs for latency, throughput, and accuracy stability; error budgets; blameless postmortems; chaos testing; and capacity forecasting across multi-datacenter and on-prem environments.\n\n - Mentor mid-level SREs, support critical incident escalations, and use production pain points to prioritize the highest-leverage automation work.\n\n - Measure and drive impact through clear metrics, including toil reduction, deployment velocity, SLO compliance, MTTR, and adoption of self-service workflows.\n\nRequired Experience & Skills\n\n - 8+ years in SRE, infrastructure engineering, or platform engineering, with a strong record of improving automation and reliability at large scale in FAANG, hyperscaler, or similarly demanding environments.\n\n - Deep expertise operating large scale heterogenous clusters with a proprietary cloud control plane\n\n - Proven track record designing and delivering CI/CD or GitOps systems using Argo CD or similar tools, with strong safety and observability built in.\n\n - Hands-on experience with observability systems such as Loki, Tempo, Mimir, and Prometheus\n\n - Ability to lead complex projects end to end, influence cross-functional stakeholders, and communicate technical direction clearly.\n\nNice-to-Haves\n\n - Experience with Bazel or other large-scale build systems in production.\n\n - Background in AI/ML inference systems, including model serving runtimes, GPU or wafer-scale orchestration, latency and accuracy SLOs, or drift monitoring.\n\n - Prior work on predictive autoscaling, chaos engineering, or cost-aware capacity planning for compute-intensive workloads.\n\nLocation\n\n - SF Bay Area\n\n - Toronto\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"ae5daf29-d7d0-440e-b41f-c6f0a67489f3","title":"Site Reliability Engineer - Ops & Automation","department":"Software Engineering ","team":"Inference Service","employmentType":"FullTime","location":"United States and Canada","secondaryLocations":[],"publishedAt":"2025-10-14T20:24:04.050+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":null,"jobUrl":"https://jobs.ashbyhq.com/cerebras/ae5daf29-d7d0-440e-b41f-c6f0a67489f3","applyUrl":"https://jobs.ashbyhq.com/cerebras/ae5daf29-d7d0-440e-b41f-c6f0a67489f3/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About the Role:
We are building a high-performance SRE function to support one of the world’s fastest-growing AI inference services, powered by the Wafer-Scale Engine (WSE), helping deliver infrastructure for frontier-class models from leading model builders such as OpenAI.
This role offers immediate ownership of real production systems at a growing scale, direct mentorship from seasoned engineers, and close collaboration with incoming Staff SREs who will focus on long-term automation. After ~1 month of shared hands-on operations with the Staff engineers, you’ll primarily operate the current setup, bring up new capacity in high-stakes environments and help bring new continuous delivery pipelines into production use.
If you thrive in high-ownership SRE roles at scale and want to help shape a team from the ground up in cutting-edge AI Inference infrastructure, this is your chance.
This role does not require 24/7 on-call rotations.
Key Responsibilities
Remain hands-on with operational execution (releases, capacity changes, cluster upgrades) over the next year as we build robust continuous delivery pipelines and self-service capabilities
Contribute to the development of self-service CD pipelines for key workflows using our stack: Kubernetes, Bazel, Prometheus/Grafana/InfluxDB, Python, and Go.
Build reusable automation and internal developer tools that minimize operational toil and cross-team friction
Develop and extend telemetry, observability and alerting solutions to ensure operational reliability at scale
Collaborate with Cluster Ops and development teams to identify high-impact automation opportunities and iterate quickly
Contribute to reliability practices (SLOs, post-mortems, capacity planning)
Required Experience & Skills
2-4+ years in SRE with a strong operations or automation focus
Production Kubernetes experience
Solid Python or Go for building tools and automation
Proficiency with Prometheus, Grafana, and observability-driven workflows
Ability to measure and communicate impact – reliability metrics, operational toil, velocity gains
Nice-to-Have
Hands-on GitOps expertise, Argo CD / Flux or equivalent, is a plus
Experience with building continuous delivery pipelines is a strong plus
Experience with Bazel or similar build systems is a strong plus.
Familiarity with capacity planning, on-prem or multi-datacenter environments
Location
SF Bay Area
Toronto
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout the Role:\n\nWe are building a high-performance SRE function to support one of the world’s fastest-growing AI inference services, powered by the Wafer-Scale Engine (WSE), helping deliver infrastructure for frontier-class models from leading model builders such as OpenAI.\n\nThis role offers immediate ownership of real production systems at a growing scale, direct mentorship from seasoned engineers, and close collaboration with incoming Staff SREs who will focus on long-term automation. After ~1 month of shared hands-on operations with the Staff engineers, you’ll primarily operate the current setup, bring up new capacity in high-stakes environments and help bring new continuous delivery pipelines into production use.\n\nIf you thrive in high-ownership SRE roles at scale and want to help shape a team from the ground up in cutting-edge AI Inference infrastructure, this is your chance.\n\nThis role does not require 24/7 on-call rotations.\n\nKey Responsibilities\n\n - Remain hands-on with operational execution (releases, capacity changes, cluster upgrades) over the next year as we build robust continuous delivery pipelines and self-service capabilities\n\n - Contribute to the development of self-service CD pipelines for key workflows using our stack: Kubernetes, Bazel, Prometheus/Grafana/InfluxDB, Python, and Go.\n\n - Build reusable automation and internal developer tools that minimize operational toil and cross-team friction\n\n - Develop and extend telemetry, observability and alerting solutions to ensure operational reliability at scale\n\n - Collaborate with Cluster Ops and development teams to identify high-impact automation opportunities and iterate quickly\n\n - Contribute to reliability practices (SLOs, post-mortems, capacity planning)\n\nRequired Experience & Skills\n\n - 2-4+ years in SRE with a strong operations or automation focus\n\n - Production Kubernetes experience\n\n - Solid Python or Go for building tools and automation\n\n - Proficiency with Prometheus, Grafana, and observability-driven workflows\n\n - Ability to measure and communicate impact – reliability metrics, operational toil, velocity gains\n\nNice-to-Have\n\n - Hands-on GitOps expertise, Argo CD / Flux or equivalent, is a plus\n\n - Experience with building continuous delivery pipelines is a strong plus\n\n - Experience with Bazel or similar build systems is a strong plus.\n\n - Familiarity with capacity planning, on-prem or multi-datacenter environments\n\nLocation\n\n - SF Bay Area\n\n - Toronto\n\n \n\n \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"ea44d96f-37e9-4d59-8749-621013176832","title":"Senior Runtime Engineer","department":"Software Engineering ","team":"Inference Core","employmentType":"FullTime","location":"United States and Canada","secondaryLocations":[],"publishedAt":"2025-10-28T13:38:32.141+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":null,"jobUrl":"https://jobs.ashbyhq.com/cerebras/ea44d96f-37e9-4d59-8749-621013176832","applyUrl":"https://jobs.ashbyhq.com/cerebras/ea44d96f-37e9-4d59-8749-621013176832/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
We are building the next generation of large-scale AI systems that power training and inference workloads at unprecedented scale and efficiency.
You will design and develop high-performance distributed software that orchestrates massive compute and data pipelines across heterogeneous clusters. Your work will push the limits of concurrency, throughput, and scalability—enabling efficient execution of models at massive scale. This role sits at the intersection of systems engineering and machine learning performance, demanding both architectural depth and low-level implementation skills. You will help shape how models are executed and optimized end-to-end, from data ingestion to distributed execution, across cutting-edge hardware platforms.
We’re hiring for runtime roles across both Training and Inference.
Responsibilities
Design and implement distributed runtime components to efficiently manage large-scale execution workloads.
Develop and optimize high-performance data and communication pipelines that fully utilize CPU, memory, storage, and network resources.
Enable scalable execution across multiple compute nodes, ensuring high concurrency and minimal bottlenecks.
Collaborate closely with ML and compiler teams to integrate new model architectures, training regimes, and hardware-specific optimizations.
Diagnose and resolve complex performance issues across the software stack using profiling and instrumentation tools.
Contribute to overall system design, architecture reviews, and roadmap planning for large-scale AI workloads.
Skills & Qualifications
3+ years of experience developing high-performance or distributed system software.
Strong programming skills in C/C++, with expertise in multi-threading, memory management, and performance optimization.
Experience with distributed systems, networking, or inter-process communication.
Solid understanding of data structures, concurrency, and system-level resource management (CPU, I/O, and memory).
Proven ability to debug, profile, and optimize code across scales—from threads to clusters.
Bachelor’s, Master’s, or equivalent experience in Computer Science, Electrical Engineering, or related field.
Preferred Skills & Qualifications
Familiarity with machine learning training or inference pipelines, especially distributed training and large-model scaling.
Exposure to Python and PyTorch, particularly in the context of model training or performance tuning.
Experience with compiler internals, custom hardware interfaces, or low-level protocol design.
Prior work on high-performance clusters, HPC systems, or custom hardware/software co-design.
Deep curiosity about how to unlock new levels of performance for large-scale AI workloads.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n \n\nAbout The Role\n\nWe are building the next generation of large-scale AI systems that power training and inference workloads at unprecedented scale and efficiency.\n\nYou will design and develop high-performance distributed software that orchestrates massive compute and data pipelines across heterogeneous clusters. Your work will push the limits of concurrency, throughput, and scalability—enabling efficient execution of models at massive scale. This role sits at the intersection of systems engineering and machine learning performance, demanding both architectural depth and low-level implementation skills. You will help shape how models are executed and optimized end-to-end, from data ingestion to distributed execution, across cutting-edge hardware platforms.\n\nWe’re hiring for runtime roles across both Training and Inference.\n\nResponsibilities\n\n - Design and implement distributed runtime components to efficiently manage large-scale execution workloads.\n\n - Develop and optimize high-performance data and communication pipelines that fully utilize CPU, memory, storage, and network resources.\n\n - Enable scalable execution across multiple compute nodes, ensuring high concurrency and minimal bottlenecks.\n\n - Collaborate closely with ML and compiler teams to integrate new model architectures, training regimes, and hardware-specific optimizations.\n\n - Diagnose and resolve complex performance issues across the software stack using profiling and instrumentation tools.\n\n - Contribute to overall system design, architecture reviews, and roadmap planning for large-scale AI workloads.\n\nSkills & Qualifications\n\n - 3+ years of experience developing high-performance or distributed system software.\n\n - Strong programming skills in C/C++, with expertise in multi-threading, memory management, and performance optimization.\n\n - Experience with distributed systems, networking, or inter-process communication.\n\n - Solid understanding of data structures, concurrency, and system-level resource management (CPU, I/O, and memory).\n\n - Proven ability to debug, profile, and optimize code across scales—from threads to clusters.\n\n - Bachelor’s, Master’s, or equivalent experience in Computer Science, Electrical Engineering, or related field.\n\nPreferred Skills & Qualifications\n\n - Familiarity with machine learning training or inference pipelines, especially distributed training and large-model scaling.\n\n - Exposure to Python and PyTorch, particularly in the context of model training or performance tuning.\n\n - Experience with compiler internals, custom hardware interfaces, or low-level protocol design.\n\n - Prior work on high-performance clusters, HPC systems, or custom hardware/software co-design.\n\n - Deep curiosity about how to unlock new levels of performance for large-scale AI workloads.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"088ab192-e04a-4819-8152-0d0f8c015299","title":"Principal Engineer, AI Inference Reliability","department":"Software Engineering ","team":"Inference Service","employmentType":"FullTime","location":"United States and Canada","secondaryLocations":[],"publishedAt":"2025-10-29T02:39:37.801+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":null,"jobUrl":"https://jobs.ashbyhq.com/cerebras/088ab192-e04a-4819-8152-0d0f8c015299","applyUrl":"https://jobs.ashbyhq.com/cerebras/088ab192-e04a-4819-8152-0d0f8c015299/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About the role
We’re looking for a hands-on Reliability Tech Lead (IC) to own the mission of making Cerebras Inference the most reliable AI service in the world. You will drive reliability strategy and execution across our inference stack, from client SDKs and public-cloud multi-region deployments to wafer-scale systems in specialized data centers.
In this role, you will define SLOs and incident-response frameworks, design and implement reliability mechanisms at scale, and partner across hundreds of engineers to ensure our service meets world-class reliability standards.
If you are passionate about building and operating massive-scale, low-latency, high-reliability distributed systems, we want to hear from you.
Responsibilities:
Define and drive reliability strategy: establish SLOs and ensure alignment across engineering.
Design and implement reliability mechanisms: build and evolve systems for fault detection, graceful degradation, failover, throttling, and recovery across multiple regions and data centers.
Lead large-scale incident management: own postmortems, root-cause analysis, and prevention loops for reliability-related incidents.
Architect for reliability and observability: influence system design for redundancy, durability, and debuggability.
Develop reliability tooling: create internal tools and frameworks for chaos testing, load simulation, and distributed fault injection.
Collaborate broadly: work across software, infrastructure, and hardware teams to ensure reliability is embedded into every layer of our inference service.
Monitor and communicate reliability metrics: build dashboards and alerts that measure service health and provide actionable insights.
Mentor and influence: guide engineers and set best practices for designing, testing, and operating reliable large-scale systems.
Skills & Qualifications:
Bachelor's or master's degree in computer science or related field.
7+ years of experience in backend, infrastructure, or reliability engineering for large-scale distributed systems.
Strong programming skills in at least one popular backend programming language such as Python, C++, Go, or Rust.
Deep and hard-earned experience of reliability principles: SLO/SLI/SLA design, incident response, and postmortem culture.
Excellent communication and cross-functional leadership skills.
Bonus: prior experience building large-scale AI infrastructure systems.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout the role \n\nWe’re looking for a hands-on Reliability Tech Lead (IC) to own the mission of making Cerebras Inference the most reliable AI service in the world. You will drive reliability strategy and execution across our inference stack, from client SDKs and public-cloud multi-region deployments to wafer-scale systems in specialized data centers. \n\nIn this role, you will define SLOs and incident-response frameworks, design and implement reliability mechanisms at scale, and partner across hundreds of engineers to ensure our service meets world-class reliability standards. \n\nIf you are passionate about building and operating massive-scale, low-latency, high-reliability distributed systems, we want to hear from you. \n\nResponsibilities: \n\n - Define and drive reliability strategy: establish SLOs and ensure alignment across engineering. \n\n - Design and implement reliability mechanisms: build and evolve systems for fault detection, graceful degradation, failover, throttling, and recovery across multiple regions and data centers. \n\n - Lead large-scale incident management: own postmortems, root-cause analysis, and prevention loops for reliability-related incidents. \n\n - Architect for reliability and observability: influence system design for redundancy, durability, and debuggability. \n\n - Develop reliability tooling: create internal tools and frameworks for chaos testing, load simulation, and distributed fault injection. \n\n - Collaborate broadly: work across software, infrastructure, and hardware teams to ensure reliability is embedded into every layer of our inference service. \n\n - Monitor and communicate reliability metrics: build dashboards and alerts that measure service health and provide actionable insights. \n\n - Mentor and influence: guide engineers and set best practices for designing, testing, and operating reliable large-scale systems. \n\nSkills & Qualifications: \n\n - Bachelor's or master's degree in computer science or related field. \n\n - 7+ years of experience in backend, infrastructure, or reliability engineering for large-scale distributed systems. \n\n - Strong programming skills in at least one popular backend programming language such as Python, C++, Go, or Rust. \n\n - Deep and hard-earned experience of reliability principles: SLO/SLI/SLA design, incident response, and postmortem culture. \n\n - Excellent communication and cross-functional leadership skills. \n\n - Bonus: prior experience building large-scale AI infrastructure systems. \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"1c8cdbc4-bd74-46df-9645-bb910eaa7a37","title":"Software Engineer, GPU Inference","department":"Software Engineering ","team":"Inference Service","employmentType":"FullTime","location":"United States and Canada","secondaryLocations":[],"publishedAt":"2025-11-25T18:10:40.280+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":null,"jobUrl":"https://jobs.ashbyhq.com/cerebras/1c8cdbc4-bd74-46df-9645-bb910eaa7a37","applyUrl":"https://jobs.ashbyhq.com/cerebras/1c8cdbc4-bd74-46df-9645-bb910eaa7a37/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Cerebras is building a new generation of disaggregated AI inference systems that combine GPU-accelerated prefill with ultra-fast decode on the Cerebras Wafer-Scale Engine.
We are hiring a Software Engineer to productionize and optimize our GPU serving stack, working across our custom inference APIs, the vLLM serving runtime, the AMD ROCm software stack, and rack-scale AMD GPU infrastructure, to make this new serving path reliable, numerically correct, observable, and exceptionally performant.
You will write production code, establish operational practices for a new accelerator fleet, and drive improvements in time to first token, throughput, tail latency, and capacity efficiency. This is a hands-on role requiring deep debugging and optimization across application, runtime, distributed systems, and hardware layers.
Productionize the GPU inference stack. Design, build, deploy, and maintain the complete GPU prefill path, spanning API services, model-serving workers, vLLM, PyTorch, ROCm, GPU nodes, networking, and rack-scale infrastructure.
Own GPU operational readiness. Establish deployment, upgrade, rollback, health-checking, capacity-management, and failure-recovery practices for the AMD GPU fleet. Build automation that makes driver, firmware, runtime, model, and container compatibility explicit and reproducible.
Drive reliability in production. Define service-level indicators and objectives for GPU-backed inference. Improve fault isolation, graceful degradation, automated recovery, incident response, and post-incident remediation across the serving stack.
Improve inference performance. Profile and optimize time to first token, request throughput, tokens per second per GPU, tail latency, GPU utilization, memory efficiency, and rack-level capacity under representative production workloads.
Optimize model-serving behavior. Tune and improve scheduling, continuous batching, prefix caching, KV-cache management, tensor and expert parallelism, request admission, quantization, graph execution, and distributed communication.
Debug across system layers. Diagnose complex failures and performance regressions across application code, vLLM, PyTorch, ROCm/HIP, collective communication libraries, kernels, drivers, firmware, networking, and hardware.
Ensure numerical correctness. Build validation and regression infrastructure for model quality, numerical accuracy, precision changes, quantization, determinism, and compatibility across software and hardware releases.
Build performance and correctness infrastructure. Develop representative benchmarks, workload replay tools, profiling automation, release qualification, dashboards, and regression gates. Turn one-off investigations into repeatable engineering systems.
5+ years of software engineering experience, including substantial individual-contributor ownership of complex production systems.
Experience building, operating, or optimizing production inference systems for large language models, multimodal models, or similarly demanding GPU workloads.
Strong programming ability in C++ and Python, including experience with multithreading, concurrency, memory management, and performance-sensitive software.
Hands-on experience with a high-performance model-serving framework such as vLLM, SGLang, TensorRT-LLM, Triton Inference Server, or an equivalent internally developed system.
Strong understanding of GPU execution and performance, including asynchronous execution, memory movement, synchronization, kernel launches, communication overhead, and profiling methodology.
Experience debugging distributed systems across multiple layers rather than treating the serving framework or accelerator runtime as a black box.
Experience with Linux, containers, Kubernetes or comparable orchestration systems, observability, CI/CD, and operating latency-sensitive services in production.
Ability to design rigorous benchmarks, interpret noisy performance results, identify bottlenecks, and translate findings into production improvements.
Strong communication and technical leadership skills, with a demonstrated ability to drive ambiguous cross-functional projects to completion.
Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or a related discipline, or equivalent practical experience.
Experience with AMD Instinct accelerators and the ROCm ecosystem, including HIP, RCCL, rocprofiler, AMD SMI, AITER, hipBLASLt, Composable Kernel, or related libraries and tools.
Deep CUDA experience that demonstrates an ability to transfer GPU systems knowledge across accelerator platforms.
Experience modifying or contributing to vLLM, SGLang, PyTorch, Triton, TensorRT-LLM, or another open-source ML systems project.
Experience optimizing prefill-heavy or disaggregated prefill/decode inference architectures.
Understanding of KV-cache transfer, prefix caching, continuous batching, chunked prefill, request scheduling, and memory-aware admission control.
Experience with multi-GPU and multi-node inference, including tensor parallelism, pipeline parallelism, expert parallelism, RDMA, collective communication, and failure handling.
Experience optimizing Mixture-of-Experts or multimodal models.
Knowledge of GPU kernel optimization, operator fusion, graph capture, attention kernels, GEMM tuning, and communication/computation overlap.
Experience with reduced-precision inference and quantization formats such as BF16, FP8, FP4, INT8, or INT4, including validation of their numerical and model-quality effects.
Experience building numerical-comparison, determinism, model-validation, or performance-regression test systems.
Experience collaborating directly with accelerator vendors, framework maintainers, or open-source communities.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n\nABOUT THE ROLE\n\nCerebras is building a new generation of disaggregated AI inference systems https://www.cerebras.ai/press-release/amd-and-cerebras-announce-industry-leading-ultra-low-latency-and-high-throughput-ai-inference that combine GPU-accelerated prefill with ultra-fast decode on the Cerebras Wafer-Scale Engine.\n\nWe are hiring a Software Engineer to productionize and optimize our GPU serving stack, working across our custom inference APIs, the vLLM serving runtime, the AMD ROCm software stack, and rack-scale AMD GPU infrastructure, to make this new serving path reliable, numerically correct, observable, and exceptionally performant.\n\nYou will write production code, establish operational practices for a new accelerator fleet, and drive improvements in time to first token, throughput, tail latency, and capacity efficiency. This is a hands-on role requiring deep debugging and optimization across application, runtime, distributed systems, and hardware layers.\n\n\nRESPONSIBILITIES\n\n - Productionize the GPU inference stack. Design, build, deploy, and maintain the complete GPU prefill path, spanning API services, model-serving workers, vLLM, PyTorch, ROCm, GPU nodes, networking, and rack-scale infrastructure.\n\n - Own GPU operational readiness. Establish deployment, upgrade, rollback, health-checking, capacity-management, and failure-recovery practices for the AMD GPU fleet. Build automation that makes driver, firmware, runtime, model, and container compatibility explicit and reproducible.\n\n - Drive reliability in production. Define service-level indicators and objectives for GPU-backed inference. Improve fault isolation, graceful degradation, automated recovery, incident response, and post-incident remediation across the serving stack.\n\n - Improve inference performance. Profile and optimize time to first token, request throughput, tokens per second per GPU, tail latency, GPU utilization, memory efficiency, and rack-level capacity under representative production workloads.\n\n - Optimize model-serving behavior. Tune and improve scheduling, continuous batching, prefix caching, KV-cache management, tensor and expert parallelism, request admission, quantization, graph execution, and distributed communication.\n\n - Debug across system layers. Diagnose complex failures and performance regressions across application code, vLLM, PyTorch, ROCm/HIP, collective communication libraries, kernels, drivers, firmware, networking, and hardware.\n\n - Ensure numerical correctness. Build validation and regression infrastructure for model quality, numerical accuracy, precision changes, quantization, determinism, and compatibility across software and hardware releases.\n\n - Build performance and correctness infrastructure. Develop representative benchmarks, workload replay tools, profiling automation, release qualification, dashboards, and regression gates. Turn one-off investigations into repeatable engineering systems.\n\n\nMINIMUM QUALIFICATIONS\n\n - 5+ years of software engineering experience, including substantial individual-contributor ownership of complex production systems.\n\n - Experience building, operating, or optimizing production inference systems for large language models, multimodal models, or similarly demanding GPU workloads.\n\n - Strong programming ability in C++ and Python, including experience with multithreading, concurrency, memory management, and performance-sensitive software.\n\n - Hands-on experience with a high-performance model-serving framework such as vLLM, SGLang, TensorRT-LLM, Triton Inference Server, or an equivalent internally developed system.\n\n - Strong understanding of GPU execution and performance, including asynchronous execution, memory movement, synchronization, kernel launches, communication overhead, and profiling methodology.\n\n - Experience debugging distributed systems across multiple layers rather than treating the serving framework or accelerator runtime as a black box.\n\n - Experience with Linux, containers, Kubernetes or comparable orchestration systems, observability, CI/CD, and operating latency-sensitive services in production.\n\n - Ability to design rigorous benchmarks, interpret noisy performance results, identify bottlenecks, and translate findings into production improvements.\n\n - Strong communication and technical leadership skills, with a demonstrated ability to drive ambiguous cross-functional projects to completion.\n\n - Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or a related discipline, or equivalent practical experience.\n\n\nPREFERRED QUALIFICATIONS\n\n - Experience with AMD Instinct accelerators and the ROCm ecosystem, including HIP, RCCL, rocprofiler, AMD SMI, AITER, hipBLASLt, Composable Kernel, or related libraries and tools.\n\n - Deep CUDA experience that demonstrates an ability to transfer GPU systems knowledge across accelerator platforms.\n\n - Experience modifying or contributing to vLLM, SGLang, PyTorch, Triton, TensorRT-LLM, or another open-source ML systems project.\n\n - Experience optimizing prefill-heavy or disaggregated prefill/decode inference architectures.\n\n - Understanding of KV-cache transfer, prefix caching, continuous batching, chunked prefill, request scheduling, and memory-aware admission control.\n\n - Experience with multi-GPU and multi-node inference, including tensor parallelism, pipeline parallelism, expert parallelism, RDMA, collective communication, and failure handling.\n\n - Experience optimizing Mixture-of-Experts or multimodal models.\n\n - Knowledge of GPU kernel optimization, operator fusion, graph capture, attention kernels, GEMM tuning, and communication/computation overlap.\n\n - Experience with reduced-precision inference and quantization formats such as BF16, FP8, FP4, INT8, or INT4, including validation of their numerical and model-quality effects.\n\n - Experience building numerical-comparison, determinism, model-validation, or performance-regression test systems.\n\n - Experience collaborating directly with accelerator vendors, framework maintainers, or open-source communities.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"915ed244-bc69-48fb-bbc0-9347d2f32fa3","title":"Lead RTL Design Engineer","department":"Hardware","team":"Silicon","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2026-08-07T21:00:18.824+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/915ed244-bc69-48fb-bbc0-9347d2f32fa3","applyUrl":"https://jobs.ashbyhq.com/cerebras/915ed244-bc69-48fb-bbc0-9347d2f32fa3/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
As a lead front-end design engineer, you will be a key part of the world-class team designing and developing the next generations of the Cerebras Wafer Scale Engine (WSE).
This role requires deep expertise in RTL design and integration, with a strong focus on delivering high-performance, power-efficient, and scalable solutions. The role also requires close collaboration and management of external ASIC vendor. You will collaborate closely with the design verification, physical design, software and system teams to bring innovative semiconductor architectures from concept to production, addressing the unique challenges of building WSE systems.
Responsibilities
Drive all aspects of chip design, including Functional Specification, Micro-architecture, RTL development, Synthesis.
Managing external ASIC vendor through product development cycle.
Work closely with PD team members for design closure to meet PPA goals.
Work closely with Design verification and DFT teams for achieving the best functional and test coverage.
Work with software and system teams to understand opportunities to deliver optimal performance and feature set for the product.
Debug silicon-level functional, timing, and power issues during bring up.
Requirements
Master’s degree in Computer Science, Electrical Engineering, or equivalent.
Can work in a hybrid work environment.
8-15 years of experience in delivering complex, high performance high quality RTL designs.
Experience with Front End Chip integration and third-party IP integration.
Demonstrated experience in networking, high-performance computing, machine learning or related fields.
Proven track record of multiple silicon success.
Experience collaborating and managing external vendors.
Experience with designing/integrating high speed IO.
Networking stack experience including TCP/IP, RDMA and Ethernet.
Knowledge of PCIe, CPU interfaces and Serdes technology.
Working knowledge of scripting tools : Python, TCL.
Assets
Experience with FPGA development toolchain, including Place and Route, Floor planning and Timing Analysis is a plus.
The base salary range for this position is $175,000 to $275,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nAs a lead front-end design engineer, you will be a key part of the world-class team designing and developing the next generations of the Cerebras Wafer Scale Engine (WSE). \n\nThis role requires deep expertise in RTL design and integration, with a strong focus on delivering high-performance, power-efficient, and scalable solutions. The role also requires close collaboration and management of external ASIC vendor. You will collaborate closely with the design verification, physical design, software and system teams to bring innovative semiconductor architectures from concept to production, addressing the unique challenges of building WSE systems.\n\n \n\nResponsibilities\n\n - Drive all aspects of chip design, including Functional Specification, Micro-architecture, RTL development, Synthesis.\n\n - Managing external ASIC vendor through product development cycle.\n\n - Work closely with PD team members for design closure to meet PPA goals.\n\n - Work closely with Design verification and DFT teams for achieving the best functional and test coverage.\n\n - Work with software and system teams to understand opportunities to deliver optimal performance and feature set for the product.\n\n - Debug silicon-level functional, timing, and power issues during bring up.\n\nRequirements\n\n - Master’s degree in Computer Science, Electrical Engineering, or equivalent.\n\n - Can work in a hybrid work environment. \n\n - 8-15 years of experience in delivering complex, high performance high quality RTL designs.\n\n - Experience with Front End Chip integration and third-party IP integration.\n\n - Demonstrated experience in networking, high-performance computing, machine learning or related fields.\n\n - Proven track record of multiple silicon success.\n\n - Experience collaborating and managing external vendors.\n\n - Experience with designing/integrating high speed IO.\n\n - Networking stack experience including TCP/IP, RDMA and Ethernet.\n\n - Knowledge of PCIe, CPU interfaces and Serdes technology.\n\n - Working knowledge of scripting tools : Python, TCL.\n\nAssets\n\n - Experience with FPGA development toolchain, including Place and Route, Floor planning and Timing Analysis is a plus.\n\n The base salary range for this position is $175,000 to $275,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.\n\n \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"d4a6507d-8908-4ea5-ac3a-0815533e2512","title":"Network Architect","department":"Software Engineering ","team":"Cluster","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2025-11-13T15:28:07.028+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/d4a6507d-8908-4ea5-ac3a-0815533e2512","applyUrl":"https://jobs.ashbyhq.com/cerebras/d4a6507d-8908-4ea5-ac3a-0815533e2512/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
As a Network Architect on the Cluster Architecture Team, you will work closely with the vendors, internal networking teams and industry peers to develop best-in-class front-end datacenter and interconnect architecture of the current and future generations of the Cerebras AI clusters. You will be responsible for developing proof-of-concept of new network designs and features enabling resilient and reliable network for AI workloads. The role will require cross-functional collaboration and interaction with diverse hardware components (e.g., network devices and the Wafer-Scale Engine) as well as software at several layers of the stack, from host-side networking to cluster-level coordination. The role also requires understanding of network monitoring systems and network debugging methodologies.
Responsibilities
Design and architect front-end network fabrics for AI/ML and HPC systems.
Identify and resolve performance and efficiency bottlenecks, ensuring high resource utilization, low latency, and high-throughput communication.
Lead cross-functional technical projects spanning multiple teams and integrating diverse software and hardware components to deliver advanced networking technologies.
Foster clear and effective communication across teams and stakeholders.
Collaborate with vendors and industry partners to shape network hardware and feature roadmaps.
Represent Cerebras in industry forums and technical communities.
Serve as the central point of contact for network reliability issues.
Skills & Qualifications
Ph.D. in Computer Science or Electrical Engineering + 10 years industry experience or Master’s in CS or EE + 15 years industry experience.
8+ Years of experience in large scale network designs in datacenter and cloud environments.
Extensive experience debugging networking issues in large distributed systems environment with multiple networking platforms and protocols.
Experience of managing and leading multi-phase and multi-team projects.
Networking platforms like Juniper, Arista, Cisco, Open box architectures (Sonic, FOBSS).
Networking protocols like VXLAN, EVPN, RoCE, BGP, DCQCN, PFC, Streaming telemetry.
Familiarity with automation languages like Python, or Go.
Familiarity with Network visibility and management systems.
Prior experience in hyperscalers or cloud service providers is strongly preferred.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nAs a Network Architect on the Cluster Architecture Team, you will work closely with the vendors, internal networking teams and industry peers to develop best-in-class front-end datacenter and interconnect architecture of the current and future generations of the Cerebras AI clusters. You will be responsible for developing proof-of-concept of new network designs and features enabling resilient and reliable network for AI workloads. The role will require cross-functional collaboration and interaction with diverse hardware components (e.g., network devices and the Wafer-Scale Engine) as well as software at several layers of the stack, from host-side networking to cluster-level coordination. The role also requires understanding of network monitoring systems and network debugging methodologies.\n\nResponsibilities\n\n - Design and architect front-end network fabrics for AI/ML and HPC systems.\n\n - Identify and resolve performance and efficiency bottlenecks, ensuring high resource utilization, low latency, and high-throughput communication.\n\n - Lead cross-functional technical projects spanning multiple teams and integrating diverse software and hardware components to deliver advanced networking technologies.\n\n - Foster clear and effective communication across teams and stakeholders.\n\n - Collaborate with vendors and industry partners to shape network hardware and feature roadmaps.\n\n - Represent Cerebras in industry forums and technical communities.\n\n - Serve as the central point of contact for network reliability issues.\n\nSkills & Qualifications\n\n - Ph.D. in Computer Science or Electrical Engineering + 10 years industry experience or Master’s in CS or EE + 15 years industry experience.\n\n - 8+ Years of experience in large scale network designs in datacenter and cloud environments.\n\n - Extensive experience debugging networking issues in large distributed systems environment with multiple networking platforms and protocols.\n\n - Experience of managing and leading multi-phase and multi-team projects.\n\n - Networking platforms like Juniper, Arista, Cisco, Open box architectures (Sonic, FOBSS).\n\n - Networking protocols like VXLAN, EVPN, RoCE, BGP, DCQCN, PFC, Streaming telemetry.\n\n - Familiarity with automation languages like Python, or Go.\n\n - Familiarity with Network visibility and management systems.\n\n - Prior experience in hyperscalers or cloud service providers is strongly preferred.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"58cebd9f-5a5c-4435-843a-aca160d66a32","title":"Principal ML Investigator","department":"Software Engineering ","team":"Cluster","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2025-12-12T14:22:36.817+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/58cebd9f-5a5c-4435-843a-aca160d66a32","applyUrl":"https://jobs.ashbyhq.com/cerebras/58cebd9f-5a5c-4435-843a-aca160d66a32/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
Cerebras is adding an ML team that can focus on a new ML effort that can align with existing teams. We are seeking a principal investigator who will partner with our ML leaders to formulate the new effort and to build up the new team and capabilities. This new team would coordinate with our current ML teams: Field ML, which works directly with customers, Applied ML, which builds new ML capabilities and applications for customers, and Core ML, which adapts ML algorithms to find unique capabilities of Cerebras hardware. The new team could take up the same or complementary responsibilities.
We would like the new team to work on some of the following areas:
Post-training and reinforcement learning: Techniques used to improve model deployment quality through further training, tuning, RL, and focus on particular downstream tasks;
Dataset curation and optimization: Techniques to collect and select high-quality data, which can help models to train or tune more quickly or to higher quality;
LLM Pretraining: Techniques to ensure stability and compute-efficiency while pretraining high quality models. May include training dynamics, parameterizations, numerics, or others;
Sparsity: Techniques to sparsify models or data that improve training time-to-quality, or optimize inference speed or throughput;
Domains: Coding agents, reasoning agents, generative language, image, video.
Principal Investigator Responsibilities
Build up a team capable of industry research and advanced development.
Organize various advanced development topics into cohesive agenda.
Adapt novel algorithms and model architectures to run on the Cerebras platform.
Systematically train, tune, and evaluate models to guide/advise production scenarios.
Collaborate with other teams to co-design next-generation hardware and software architectures.
Collaborate with external partners (customers, academic) to drive insight and credibility.
Skills & Qualifications
PhD in Computer Science or related field.
Strong grasp of ML theory in one or more of the above areas.
Proven experience engineering ML systems for scale or production deployment.
Experience leading a team of researchers or engineers.
Preferred Skills & Qualifications
Track record of patents or publications in top-tier conferences or journals.
Experience with large language models (e.g., GPT family, Llama).
Experience with distributed training concepts and frameworks.
Experience in training speed optimizations, such as model architecture transformations to target hardware, or low-level kernel development (e.g., Triton).
Ability to analytically model or optimize system performance.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nCerebras is adding an ML team that can focus on a new ML effort that can align with existing teams. We are seeking a principal investigator who will partner with our ML leaders to formulate the new effort and to build up the new team and capabilities. This new team would coordinate with our current ML teams: Field ML, which works directly with customers, Applied ML, which builds new ML capabilities and applications for customers, and Core ML, which adapts ML algorithms to find unique capabilities of Cerebras hardware. The new team could take up the same or complementary responsibilities.\n\nWe would like the new team to work on some of the following areas:\n\n - Post-training and reinforcement learning: Techniques used to improve model deployment quality through further training, tuning, RL, and focus on particular downstream tasks;\n\n - Dataset curation and optimization: Techniques to collect and select high-quality data, which can help models to train or tune more quickly or to higher quality;\n\n - LLM Pretraining: Techniques to ensure stability and compute-efficiency while pretraining high quality models. May include training dynamics, parameterizations, numerics, or others;\n\n - Sparsity: Techniques to sparsify models or data that improve training time-to-quality, or optimize inference speed or throughput;\n\n - Domains: Coding agents, reasoning agents, generative language, image, video.\n\nPrincipal Investigator Responsibilities\n\n - Build up a team capable of industry research and advanced development.\n\n - Organize various advanced development topics into cohesive agenda.\n\n - Adapt novel algorithms and model architectures to run on the Cerebras platform.\n\n - Systematically train, tune, and evaluate models to guide/advise production scenarios.\n\n - Collaborate with other teams to co-design next-generation hardware and software architectures.\n\n - Collaborate with external partners (customers, academic) to drive insight and credibility.\n\nSkills & Qualifications\n\n - PhD in Computer Science or related field.\n\n - Strong grasp of ML theory in one or more of the above areas.\n\n - Proven experience engineering ML systems for scale or production deployment.\n\n - Experience leading a team of researchers or engineers.\n\nPreferred Skills & Qualifications\n\n - Track record of patents or publications in top-tier conferences or journals.\n\n - Experience with large language models (e.g., GPT family, Llama).\n\n - Experience with distributed training concepts and frameworks.\n\n - Experience in training speed optimizations, such as model architecture transformations to target hardware, or low-level kernel development (e.g., Triton).\n\n - Ability to analytically model or optimize system performance.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"987d7f64-c957-4c8f-b89d-2f9d64738507","title":"CoDesign & NextGen - New College Grad ","department":"Software Engineering ","team":"CoDesign","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2026-01-07T04:02:02.311+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/987d7f64-c957-4c8f-b89d-2f9d64738507","applyUrl":"https://jobs.ashbyhq.com/cerebras/987d7f64-c957-4c8f-b89d-2f9d64738507/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
Engineers in the CoDesign and NextGen organization work at the interface of software and hardware helping everything from high performance kernel design, next generation ASIC performance modeling and tuning, new system bringup and software tuning, system robustness and simulations.
As an new engineer you'll be expected to learn the Cerebras products and platforms end to end starting at the base layer of programming the Wafer Scale Engine through kernel development, modeling performance for our software products and validating the work through exercising it on both actual hardware and simulations.
Skills & Qualifications
MS/BS in Computer Engineer, Electrical Engineering or Computer Science
Strong background in computer architecture
Strong analytical and problem solving mindset
Exposure to CPU/GPU Architecture and programming models
Experience working on CPU/GPU simulators
Exposure to performance profiling and debug on any system pipeline
Experience with C++ and Python
Exposure to and basic understanding of machine learning is desired
Location
This is a full-time, in-office position based in Sunnyvale, CA. We offer relocation support for candidates relocating to the Bay Area.
Base salary range: $145,000-$155,000 annually, depending on experience, skills, and qualifications, plus equity.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nEngineers in the CoDesign and NextGen organization work at the interface of software and hardware helping everything from high performance kernel design, next generation ASIC performance modeling and tuning, new system bringup and software tuning, system robustness and simulations.\n\n \n\nAs an new engineer you'll be expected to learn the Cerebras products and platforms end to end starting at the base layer of programming the Wafer Scale Engine through kernel development, modeling performance for our software products and validating the work through exercising it on both actual hardware and simulations.\n\nSkills & Qualifications\n\n - MS/BS in Computer Engineer, Electrical Engineering or Computer Science\n\n - Strong background in computer architecture\n\n - Strong analytical and problem solving mindset\n\n - Exposure to CPU/GPU Architecture and programming models\n\n - Experience working on CPU/GPU simulators\n\n - Exposure to performance profiling and debug on any system pipeline\n\n - Experience with C++ and Python\n\n - Exposure to and basic understanding of machine learning is desired\n\nLocation\n\nThis is a full-time, in-office position based in Sunnyvale, CA. We offer relocation support for candidates relocating to the Bay Area.\n\nBase salary range: $145,000-$155,000 annually, depending on experience, skills, and qualifications, plus equity. \n\n \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"13eec2f8-b308-40b4-8194-f3c133ccb3bc","title":"Engineering Manager, Kernel Reliability ","department":"Software Engineering ","team":"CoDesign","employmentType":"FullTime","location":"United States and Canada","secondaryLocations":[],"publishedAt":"2026-01-08T18:01:49.310+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":null,"jobUrl":"https://jobs.ashbyhq.com/cerebras/13eec2f8-b308-40b4-8194-f3c133ccb3bc","applyUrl":"https://jobs.ashbyhq.com/cerebras/13eec2f8-b308-40b4-8194-f3c133ccb3bc/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
We're looking for a deeply technical, hands-on engineering leader for our on-field Kernel Reliability team. You will lead a high performing team to tackle a critical challenge: improving the reliability of our advanced compute clusters and the underlying inference, training, and internal production services. In this role, you'll set the technical vision while staying close to the code and designing solutions that will scale to our exponentially growing system production and software service offerings. If you have proven expertise in software or hardware reliability, diagnostic tool building, or failure analysis and debugging, we want to hear from you.
Responsibilities
Provide hands-on technical leadership, owning the technical vision and roadmap for the kernel-centric reliability of our internal and customer-facing systems
Assist System and Cluster Operations teams on reducing system and service downtime after failure by providing tooling and manual intervention for failure analysis and diagnostic
Work with the Debug Team to enhance debug tools with the goal of speeding up failure analysis
Collaborate with SW teams to improve the software stack, including Kernels, to improve on-field debugging and failure analysis
Work with the ASIC an HW architecture teams to codesign the next generation architectures with reliability and ease of debug in mind
Lead, mentor, and grow a high-caliber team of engineers, fostering a culture of technical excellence and rapid execution.
Skills & Qualifications
6+ years in software engineering, with 3+ years leading teams in SW/HW reliability, debug, diagnostic, failure analysis or related fields
Expertise in parallel and distributed programming (message passing, multicore, GPU, embeded, etc.), debug and diagnostic tool development or expert usage (debuggers, core dump handling, code sanitizers, etc.), experience debugging distributed and parallel applications (deadlocks, livelocks, race conditions, etc.), deep understanding of computer architectures (instruction pipelining, multithreading, networking, etc.)
Operations & Monitoring: Strong background in monitoring and reliability engineering (incident response, post-mortem analysis, etc.)
Leadership & Collaboration: Demonstrated ability to recruit and retain high-performing teams, mentor engineers, and partner cross-functionally to deliver customer-facing products.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\n \n\nWe're looking for a deeply technical, hands-on engineering leader for our on-field Kernel Reliability team. You will lead a high performing team to tackle a critical challenge: improving the reliability of our advanced compute clusters and the underlying inference, training, and internal production services. In this role, you'll set the technical vision while staying close to the code and designing solutions that will scale to our exponentially growing system production and software service offerings. If you have proven expertise in software or hardware reliability, diagnostic tool building, or failure analysis and debugging, we want to hear from you.\n\n \n\nResponsibilities\n\n - Provide hands-on technical leadership, owning the technical vision and roadmap for the kernel-centric reliability of our internal and customer-facing systems\n\n - Assist System and Cluster Operations teams on reducing system and service downtime after failure by providing tooling and manual intervention for failure analysis and diagnostic\n\n - Work with the Debug Team to enhance debug tools with the goal of speeding up failure analysis\n\n - Collaborate with SW teams to improve the software stack, including Kernels, to improve on-field debugging and failure analysis\n\n - Work with the ASIC an HW architecture teams to codesign the next generation architectures with reliability and ease of debug in mind\n\n - Lead, mentor, and grow a high-caliber team of engineers, fostering a culture of technical excellence and rapid execution. \n\nSkills & Qualifications\n\n - 6+ years in software engineering, with 3+ years leading teams in SW/HW reliability, debug, diagnostic, failure analysis or related fields \n\n - Expertise in parallel and distributed programming (message passing, multicore, GPU, embeded, etc.), debug and diagnostic tool development or expert usage (debuggers, core dump handling, code sanitizers, etc.), experience debugging distributed and parallel applications (deadlocks, livelocks, race conditions, etc.), deep understanding of computer architectures (instruction pipelining, multithreading, networking, etc.)\n\n - Operations & Monitoring: Strong background in monitoring and reliability engineering (incident response, post-mortem analysis, etc.)\n\n - Leadership & Collaboration: Demonstrated ability to recruit and retain high-performing teams, mentor engineers, and partner cross-functionally to deliver customer-facing products.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"594d7525-be2b-4407-8649-6e4a8cd302e8","title":"Applied AI/ML Scientist","department":"Software Engineering ","team":"Software Engineering ","employmentType":"FullTime","location":"UAE ","secondaryLocations":[],"publishedAt":"2026-01-14T23:03:59.831+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":null,"jobUrl":"https://jobs.ashbyhq.com/cerebras/594d7525-be2b-4407-8649-6e4a8cd302e8","applyUrl":"https://jobs.ashbyhq.com/cerebras/594d7525-be2b-4407-8649-6e4a8cd302e8/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
As an Applied AI Scientist in the FieldML team, you will be responsible for developing and customizing large language models and more broadly large-scale deep learning models to solve specific customer problems. You won't just advise; you will build. You will bridge the gap between state-of-the-art research and real-world applications by helping customers harness the power of the Cerebras Wafer-Scale Engine (WSE) for their AI initiatives.
We are looking for experienced AI Scientists who are passionate about the \"applied\" side of machine learning - those who enjoy not just reading papers, but implementing, training, and scaling models to solve complex business and scientific problems. You will work on a diverse range of projects, from training bespoke models from scratch to fine-tuning and optimizing the latest Large Language Models (LLMs) for specific industry verticals, to designing and building components for custom agentic systems.
The ideal candidate has experience in large model training and/or post-training, a deep understanding of training dynamics and model convergence, and expertise in data curation, combined with strong communication skills.
Key Responsibilities
Customer Use Case Discovery & Project Scoping
Collaborate with customer stakeholders to identify the best approaches to their business problem with AI.
Contribute to the technical scoping of engagements, including feasibility analysis, data quality/availability/readiness assessments, and the selection of optimal model architectures.
Define project milestones, success metrics, and rigorous evaluation benchmarks to ensure the solution delivers measurable value to the customer’s business.
Custom SOTA Models and AI Systems Development
Architect and execute end-to-end training recipes for custom models, tailoring model architecture and training recipes to meet customer-specific performance and accuracy requirements.
Design and implement sophisticated adaptation strategies, including continuous pre-training on private datasets, supervised fine-tuning (SFT), and post-training alignment via RLHF or DPO.
Take full ownership of the training pipeline, from high-performance data preprocessing and tokenization to hyperparameter tuning and loss-curve analysis.
Navigate the nuances of model convergence on specialized hardware, performing deep-dive analysis into loss dynamics and gradient stability.
Scale training workloads across Cerebras clusters, ensuring efficient utilization of the hardware for multi-billion parameter models.
Build and optimize the core components of agentic systems, focusing on tool-use capabilities, long-context reasoning, and multi-step planning.
Technical Customer Leadership
Serve as an AI/ML subject matter expert during technical deep-dives, translating customer requirements into precise training recipes.
Build and maintain strong customer relationships to become their go-to AI/ML expert.
Internal Research and Engineering Collaboration
Act as the \"voice of the customer\" for internal R&D and engineering teams to drive improvements in our software stack and hardware utilization.
Partner with internal ML teams and product teams on prioritization of novel model architectures with Cerebras software stack, development of training recipes and internal case studies.
Distill customer-facing successful projects into internal playbooks, helping scale the FieldML team’s ability to deliver specialized models.
Skills And Qualifications
Education: Master’s or PhD in Computer Science, Machine Learning, or related fields.
Broad Deep Learning Expertise: Expert-level understanding of modern model architectures, including dense transformers, MoEs, multimodal and sequence models, scaling laws and training dynamics.
Hands-on Trainig Experience: Proven track record of training and/or fine-tuning large models (1B+ parameters) and direct experience with the challenges of large-scale model training.
Engineering Proficiency: Mastery of Python and PyTorch, experience with distributed training frameworks and large-scale distributed data processing pipelines and tools.
Strong Interpersonal and Communication Skills: Effective in collaborative and fast-paced team settings, able to work autonomously and within a team in a dynamic environment, managing multiple projects and pivoting as customer needs evolve. Able to present complex technical results to diverse audience - from C-level executives to research scientists, and to work collaboratively to solve customers’ unique challenges.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nAs an Applied AI Scientist in the FieldML team, you will be responsible for developing and customizing large language models and more broadly large-scale deep learning models to solve specific customer problems. You won't just advise; you will build. You will bridge the gap between state-of-the-art research and real-world applications by helping customers harness the power of the Cerebras Wafer-Scale Engine (WSE) for their AI initiatives. \n\nWe are looking for experienced AI Scientists who are passionate about the \"applied\" side of machine learning - those who enjoy not just reading papers, but implementing, training, and scaling models to solve complex business and scientific problems. You will work on a diverse range of projects, from training bespoke models from scratch to fine-tuning and optimizing the latest Large Language Models (LLMs) for specific industry verticals, to designing and building components for custom agentic systems. \n\nThe ideal candidate has experience in large model training and/or post-training, a deep understanding of training dynamics and model convergence, and expertise in data curation, combined with strong communication skills. \n\nKey Responsibilities \n\n - Customer Use Case Discovery & Project Scoping \n \n - Collaborate with customer stakeholders to identify the best approaches to their business problem with AI. \n \n - Contribute to the technical scoping of engagements, including feasibility analysis, data quality/availability/readiness assessments, and the selection of optimal model architectures. \n \n - Define project milestones, success metrics, and rigorous evaluation benchmarks to ensure the solution delivers measurable value to the customer’s business. \n\n - Custom SOTA Models and AI Systems Development \n \n - Architect and execute end-to-end training recipes for custom models, tailoring model architecture and training recipes to meet customer-specific performance and accuracy requirements. \n \n - Design and implement sophisticated adaptation strategies, including continuous pre-training on private datasets, supervised fine-tuning (SFT), and post-training alignment via RLHF or DPO. \n \n - Take full ownership of the training pipeline, from high-performance data preprocessing and tokenization to hyperparameter tuning and loss-curve analysis. \n \n - Navigate the nuances of model convergence on specialized hardware, performing deep-dive analysis into loss dynamics and gradient stability. \n \n - Scale training workloads across Cerebras clusters, ensuring efficient utilization of the hardware for multi-billion parameter models. \n \n - Build and optimize the core components of agentic systems, focusing on tool-use capabilities, long-context reasoning, and multi-step planning. \n\n - Technical Customer Leadership \n \n - Serve as an AI/ML subject matter expert during technical deep-dives, translating customer requirements into precise training recipes. \n \n - Build and maintain strong customer relationships to become their go-to AI/ML expert. \n\n - Internal Research and Engineering Collaboration \n \n - Act as the \"voice of the customer\" for internal R&D and engineering teams to drive improvements in our software stack and hardware utilization. \n \n - Partner with internal ML teams and product teams on prioritization of novel model architectures with Cerebras software stack, development of training recipes and internal case studies. \n \n - Distill customer-facing successful projects into internal playbooks, helping scale the FieldML team’s ability to deliver specialized models.\n\nSkills And Qualifications \n\n - Education: Master’s or PhD in Computer Science, Machine Learning, or related fields. \n\n - Broad Deep Learning Expertise: Expert-level understanding of modern model architectures, including dense transformers, MoEs, multimodal and sequence models, scaling laws and training dynamics. \n\n - Hands-on Trainig Experience: Proven track record of training and/or fine-tuning large models (1B+ parameters) and direct experience with the challenges of large-scale model training. \n\n - Engineering Proficiency: Mastery of Python and PyTorch, experience with distributed training frameworks and large-scale distributed data processing pipelines and tools. \n\n - Strong Interpersonal and Communication Skills: Effective in collaborative and fast-paced team settings, able to work autonomously and within a team in a dynamic environment, managing multiple projects and pivoting as customer needs evolve. Able to present complex technical results to diverse audience - from C-level executives to research scientists, and to work collaboratively to solve customers’ unique challenges. \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"538ef11a-dfaa-47f1-8557-790199a769d1","title":"Senior Product Manager, AI Models","department":"Product","team":"Product","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[{"location":"Remote (US)","address":{"postalAddress":{"addressCountry":"United States"}}}],"publishedAt":"2026-01-15T22:47:14.927+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/538ef11a-dfaa-47f1-8557-790199a769d1","applyUrl":"https://jobs.ashbyhq.com/cerebras/538ef11a-dfaa-47f1-8557-790199a769d1/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Own the Future of AI Inference
Cerebras powers the world's fastest AI inference. As the Product Manager for AI Models, you'll lead the strategic model portfolio that defines our product — deciding which models ship, how they perform, and how the world discovers them.
You'll partner directly with leading AI labs, drive launches that shape the industry, and ensure every model on our platform delivers exceptional quality at unprecedented speed.
What You'll Own
Strategic Model Portfolio
Own the models roadmap: decide which frontier and open-source models we support based on market demand, research trends, and strategic fit
Establish partnerships with top model labs, for day0 launches
Build relationships with open-source maintainers to accelerate community model adoption
Product Quality & Customer Success
Define and enforce quality standards across our model catalog through systematic evaluation frameworks
Design benchmarks and evaluations that prove our models deliver production-grade performance
Own the feedback loop: gather customer insights, identify model weaknesses, and drive improvements with engineering
Enable strategic customers to integrate our inference into their products—removing blockers and optimizing for their specific use cases
Go-to-Market Excellence
Lead high-impact model launches that generate buzz and adoption
Create compelling product marketing: demos, benchmarks, tutorials, and documentation that showcase what's possible on Cerebras
Craft technical content that resonates with developers and decision-makers alike
Technical Decision-Making
Select and prioritize performance optimizations (quantization, speculative decoding, etc.) based on customer needs and hardware capabilities
Collaborate with optimization engineers to implement techniques that maximize our speed advantage
Balance tradeoffs between quality, latency, throughput, and cost
Cross-Functional Leadership
Orchestrate launches across model enablement, optimization engineering, deployment, sales, and marketing
Drive alignment in a fast-moving environment where priorities shift based on model releases and customer needs
Be the voice of the customer to engineering and the voice of product to customers
Skills & Qualifications
What we need to see:
5+ years of experience as a product manager, currently at or above the level of Senior PM.
5+ years of total technical work experience (e.g. SWE, ML researcher, solution engineer).
Ability to thrive in a fast-paced, dynamic environment. With an entrepreneurial sense of ownership and ability to lead projects.
Knowledge and passion for the worlds of open-source models and generative AI research.
Knowledge of the community model ecosystem, including: PyTorch, Hugging Face, vLLM, and SGLang.
Highly motivated, independent, organized, and an effective communicator.
Comfortable using Python with the chat completions API, for basic model testing.
Preferred requirements
How to stand out:
Product manager experience at a model training lab or a company that implements open-source models.
Experience working with customers in a solution engineering role.
Experience writing technical marketing assets and social media, with a growing portfolio.
Experience working in a cross-functional organization, and leading projects across multiple teams.
Experience writing model quality evaluations and system prompt harnesses.
Experience writing application code in use cases such as code generation or deep research search application.
Expertise on agentic flows and current LLM model family architectures.
Understanding of model compilers and optimization.
Contributor to communities like vLLM, SGLang, PyTorch, or Hugging Face transformers.
Experience with model optimization or compression methods like quantization.
Location
Hybrid at our Sunnyvale, California or Toronto, Canada office.
Remote possible for candidates willing to travel 1-2x per quarter.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nOwn the Future of AI Inference\n\nCerebras powers the world's fastest AI inference. As the Product Manager for AI Models, you'll lead the strategic model portfolio that defines our product — deciding which models ship, how they perform, and how the world discovers them.\n\nYou'll partner directly with leading AI labs, drive launches that shape the industry, and ensure every model on our platform delivers exceptional quality at unprecedented speed.\n\nWhat You'll Own\n\nStrategic Model Portfolio\n\n - Own the models roadmap: decide which frontier and open-source models we support based on market demand, research trends, and strategic fit\n\n - Establish partnerships with top model labs, for day0 launches\n\n - Build relationships with open-source maintainers to accelerate community model adoption\n\nProduct Quality & Customer Success\n\n - Define and enforce quality standards across our model catalog through systematic evaluation frameworks\n\n - Design benchmarks and evaluations that prove our models deliver production-grade performance\n\n - Own the feedback loop: gather customer insights, identify model weaknesses, and drive improvements with engineering\n\n - Enable strategic customers to integrate our inference into their products—removing blockers and optimizing for their specific use cases\n\nGo-to-Market Excellence\n\n - Lead high-impact model launches that generate buzz and adoption\n\n - Create compelling product marketing: demos, benchmarks, tutorials, and documentation that showcase what's possible on Cerebras\n\n - Craft technical content that resonates with developers and decision-makers alike\n\nTechnical Decision-Making\n\n - Select and prioritize performance optimizations (quantization, speculative decoding, etc.) based on customer needs and hardware capabilities\n\n - Collaborate with optimization engineers to implement techniques that maximize our speed advantage\n\n - Balance tradeoffs between quality, latency, throughput, and cost\n\nCross-Functional Leadership\n\n - Orchestrate launches across model enablement, optimization engineering, deployment, sales, and marketing\n\n - Drive alignment in a fast-moving environment where priorities shift based on model releases and customer needs\n\n - Be the voice of the customer to engineering and the voice of product to customers\n\nSkills & Qualifications \n\nWhat we need to see:\n\n 1. 5+ years of experience as a product manager, currently at or above the level of Senior PM.\n\n 2. 5+ years of total technical work experience (e.g. SWE, ML researcher, solution engineer).\n\n 3. Ability to thrive in a fast-paced, dynamic environment. With an entrepreneurial sense of ownership and ability to lead projects.\n\n 4. Knowledge and passion for the worlds of open-source models and generative AI research.\n\n 5. Knowledge of the community model ecosystem, including: PyTorch, Hugging Face, vLLM, and SGLang.\n\n 6. Highly motivated, independent, organized, and an effective communicator.\n\n 7. Comfortable using Python with the chat completions API, for basic model testing.\n\nPreferred requirements \n\nHow to stand out:\n\n 1. Product manager experience at a model training lab or a company that implements open-source models.\n\n 2. Experience working with customers in a solution engineering role.\n\n 3. Experience writing technical marketing assets and social media, with a growing portfolio.\n\n 4. Experience working in a cross-functional organization, and leading projects across multiple teams.\n\n 5. Experience writing model quality evaluations and system prompt harnesses.\n\n 6. Experience writing application code in use cases such as code generation or deep research search application.\n\n 7. Expertise on agentic flows and current LLM model family architectures.\n\n 8. Understanding of model compilers and optimization.\n\n 9. Contributor to communities like vLLM, SGLang, PyTorch, or Hugging Face transformers.\n\n 10. Experience with model optimization or compression methods like quantization.\n\nLocation \n\n - Hybrid at our Sunnyvale, California or Toronto, Canada office.\n\n - Remote possible for candidates willing to travel 1-2x per quarter. \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"d65f2d36-998d-4384-8cff-36835a403ce6","title":"ML Systems Performance Engineer","department":"Software Engineering ","team":"Inference Core","employmentType":"FullTime","location":"United States and Canada","secondaryLocations":[],"publishedAt":"2026-01-21T18:30:17.035+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":null,"jobUrl":"https://jobs.ashbyhq.com/cerebras/d65f2d36-998d-4384-8cff-36835a403ce6","applyUrl":"https://jobs.ashbyhq.com/cerebras/d65f2d36-998d-4384-8cff-36835a403ce6/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Engineers on the inference performance team operate at the intersection of hardware and software, driving end-to-end model inference speed and throughput. Their work spans low-level kernel performance debugging and optimization, system-level performance analysis, performance modeling and estimation, and the development of tooling for performance projection and diagnostics.
Build performance models (kernel-level, end-to-end) to estimate the performance of state of the art and customer ML models.
Optimize and debug our kernel micro code and compiler algorithms to elevate ML model inference speed, throughput and compute utilization on the Cerebras WSE.
Debug and understand runtime performance on the system and cluster.
Develop tools and infrastructure to help visualize performance data collected from the Wafer Scale Engine and our compute cluster.
Bachelors / Masters / PhD in Electrical Engineering or Computer Science.
Strong background in computer architecture.
Exposure to and understanding of low-level deep learning / LLM math.
Strong analytical and problem-solving mindset.
3+ years of experience in a relevant domain (Computer Architecture, CPU/GPU Performance, Kernel Optimization, HPC).
Experience working on CPU/GPU simulators.
Exposure to performance profiling and debug on any system pipeline.
Comfort with C++ and Python.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n\nABOUT THE ROLE\n\nEngineers on the inference performance team operate at the intersection of hardware and software, driving end-to-end model inference speed and throughput. Their work spans low-level kernel performance debugging and optimization, system-level performance analysis, performance modeling and estimation, and the development of tooling for performance projection and diagnostics.\n\n\nRESPONSIBILITIES\n\n - Build performance models (kernel-level, end-to-end) to estimate the performance of state of the art and customer ML models.\n\n - Optimize and debug our kernel micro code and compiler algorithms to elevate ML model inference speed, throughput and compute utilization on the Cerebras WSE.\n\n - Debug and understand runtime performance on the system and cluster.\n\n - Develop tools and infrastructure to help visualize performance data collected from the Wafer Scale Engine and our compute cluster.\n\n\nREQUIREMENTS\n\n - Bachelors / Masters / PhD in Electrical Engineering or Computer Science.\n\n - Strong background in computer architecture.\n\n - Exposure to and understanding of low-level deep learning / LLM math.\n\n - Strong analytical and problem-solving mindset.\n\n - 3+ years of experience in a relevant domain (Computer Architecture, CPU/GPU Performance, Kernel Optimization, HPC).\n\n - Experience working on CPU/GPU simulators.\n\n - Exposure to performance profiling and debug on any system pipeline.\n\n - Comfort with C++ and Python.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"1fd0045d-8469-4dc6-ab13-d4fd0bf26f8b","title":"Kernel Engineer","department":"Software Engineering ","team":"Inference Core","employmentType":"FullTime","location":"United States and Canada","secondaryLocations":[],"publishedAt":"2026-02-23T15:19:15.020+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":null,"jobUrl":"https://jobs.ashbyhq.com/cerebras/1fd0045d-8469-4dc6-ab13-d4fd0bf26f8b","applyUrl":"https://jobs.ashbyhq.com/cerebras/1fd0045d-8469-4dc6-ab13-d4fd0bf26f8b/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
As a Kernel Engineer on our team, you will develop high-performance software solutions at the intersection of hardware and software, developing high-performance software for cutting-edge AI and HPC workloads. Your focus will be on implementing, optimizing, and scaling deep learning operations to fully leverage our custom, massively parallel processor architecture.
You will be part of a world-class team responsible for the design, performance tuning, and validation of foundational ML and HPC kernels. This includes building a library of parallel and distributed algorithms that maximize compute utilization and push the boundaries of training efficiency for state-of-the-art AI models. Your work will be critical to unlocking the full potential of our hardware and accelerating the pace of AI innovation.
Responsibilities
Develop design specifications for new machine learning and linear algebra kernels and mapping to the Cerebras WSE System using various parallel programming algorithms.
Develop and debug kernel library of highly optimized low level assembly instruction and C-like domain specific language routines to implement algorithms targeting the Cerebras hardware system.
Develop and debug high-performance kernel routines in low-level assembly and a custom C-like (CSL) language, implementing algorithms optimized for the Cerebras hardware system.
Using mathematical models and analysis to measure the software performance and inform design decisions.
Develop and integrate unit and system testing methodologies to verify correct functionality and performance of kernel libraries.
Study emerging trends in Machine Learning applications and help evolve Kernel library architecture to address computational challenges of the start-of-the-art Neural Networks.
Interact with chip and system architects to optimize instruction sets, microarchitecture, and IO of next generation systems.
Skills And Qualifications
Bachelor’s, Master’s, PhD or foreign equivalents in Computer Science, Computer Engineering, Mathematics, or related fields.
Understanding of hardware architecture concepts — must be comfortable learning the details of a new hardware architecture.
Skilled in C++ and Python programming languages.
Good knowledge of library and/or API development best practices.
Strong debugging skills and knowledge of debugging complex software stack.
Preferred Skills And Qualifications
Experience in kernel development and/or testing.
Familiarity with parallel algorithms and distributed memory systems.
Experience in programming accelerators such as GPUs and FPGAs.
Familiarity with Machine Learning neural networks and frameworks such as TensorFlow and PyTorch.
Familiarity with HPC kernels and their optimization.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nAs a Kernel Engineer on our team, you will develop high-performance software solutions at the intersection of hardware and software, developing high-performance software for cutting-edge AI and HPC workloads. Your focus will be on implementing, optimizing, and scaling deep learning operations to fully leverage our custom, massively parallel processor architecture.\n\nYou will be part of a world-class team responsible for the design, performance tuning, and validation of foundational ML and HPC kernels. This includes building a library of parallel and distributed algorithms that maximize compute utilization and push the boundaries of training efficiency for state-of-the-art AI models. Your work will be critical to unlocking the full potential of our hardware and accelerating the pace of AI innovation.\n\nResponsibilities\n\n - Develop design specifications for new machine learning and linear algebra kernels and mapping to the Cerebras WSE System using various parallel programming algorithms.\n\n - Develop and debug kernel library of highly optimized low level assembly instruction and C-like domain specific language routines to implement algorithms targeting the Cerebras hardware system.\n\n - Develop and debug high-performance kernel routines in low-level assembly and a custom C-like (CSL) language, implementing algorithms optimized for the Cerebras hardware system.\n\n - Using mathematical models and analysis to measure the software performance and inform design decisions.\n\n - Develop and integrate unit and system testing methodologies to verify correct functionality and performance of kernel libraries.\n\n - Study emerging trends in Machine Learning applications and help evolve Kernel library architecture to address computational challenges of the start-of-the-art Neural Networks.\n\n - Interact with chip and system architects to optimize instruction sets, microarchitecture, and IO of next generation systems.\n\nSkills And Qualifications\n\n - Bachelor’s, Master’s, PhD or foreign equivalents in Computer Science, Computer Engineering, Mathematics, or related fields.\n\n - Understanding of hardware architecture concepts — must be comfortable learning the details of a new hardware architecture.\n\n - Skilled in C++ and Python programming languages.\n\n - Good knowledge of library and/or API development best practices.\n\n - Strong debugging skills and knowledge of debugging complex software stack.\n\nPreferred Skills And Qualifications\n\n - Experience in kernel development and/or testing.\n\n - Familiarity with parallel algorithms and distributed memory systems.\n\n - Experience in programming accelerators such as GPUs and FPGAs.\n\n - Familiarity with Machine Learning neural networks and frameworks such as TensorFlow and PyTorch.\n\n - Familiarity with HPC kernels and their optimization.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"270407eb-1452-4a36-8f8c-7d64263eaa0a","title":"Staff Kernel Optimzation Engineer ","department":"Software Engineering ","team":"Voyager","employmentType":"FullTime","location":"Remote","secondaryLocations":[],"publishedAt":"2026-02-05T16:04:08.521+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":null,"jobUrl":"https://jobs.ashbyhq.com/cerebras/270407eb-1452-4a36-8f8c-7d64263eaa0a","applyUrl":"https://jobs.ashbyhq.com/cerebras/270407eb-1452-4a36-8f8c-7d64263eaa0a/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
As a Kernel Engineer on our team, you will develop high-performance software solutions at the intersection of hardware and software, developing high-performance software for cutting-edge AI and HPC workloads. Your focus will be on implementing, optimizing, and scaling deep learning operations to fully leverage our custom, massively parallel processor architecture.
You will be part of a world-class team responsible for the design, performance tuning, and validation of foundational ML and HPC kernels. This includes building a library of parallel and distributed algorithms that maximize compute utilization and push the boundaries of training efficiency for state-of-the-art AI models. Your work will be critical to unlocking the full potential of our hardware and accelerating the pace of AI innovation.
Responsibilities
Develop design specifications for new machine learning and linear algebra kernels and mapping to the Cerebras WSE System using various parallel programming algorithms.
Develop and debug kernel library of highly optimized low level assembly instruction and C-like domain specific language routines to implement algorithms targeting the Cerebras hardware system.
Develop and debug high-performance kernel routines in low-level assembly and a custom C-like (CSL) language, implementing algorithms optimized for the Cerebras hardware system.
Using mathematical models and analysis to measure the software performance and inform design decisions.
Develop and integrate unit and system testing methodologies to verify correct functionality and performance of kernel libraries.
Study emerging trends in Machine Learning applications and help evolve Kernel library architecture to address computational challenges of the start-of-the-art Neural Networks.
Interact with chip and system architects to optimize instruction sets, microarchitecture, and IO of next generation systems.
Skills And Qualifications
Bachelor’s, Master’s, PhD or foreign equivalents in Computer Science, Computer Engineering, Mathematics, or related fields.
Understanding of hardware architecture concepts — must be comfortable learning the details of a new hardware architecture.
Skilled in C++ and Python programming languages.
Good knowledge of library and/or API development best practices.
Strong debugging skills and knowledge of debugging complex software stack.
Preferred Skills And Qualifications
Experience in kernel development and/or testing.
Familiarity with parallel algorithms and distributed memory systems.
Experience in programming accelerators such as GPUs and FPGAs.
Familiarity with Machine Learning neural networks and frameworks such as TensorFlow and PyTorch.
Familiarity with HPC kernels and their optimization.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n \n\nAbout The Role\nAs a Kernel Engineer on our team, you will develop high-performance software solutions at the intersection of hardware and software, developing high-performance software for cutting-edge AI and HPC workloads. Your focus will be on implementing, optimizing, and scaling deep learning operations to fully leverage our custom, massively parallel processor architecture.\nYou will be part of a world-class team responsible for the design, performance tuning, and validation of foundational ML and HPC kernels. This includes building a library of parallel and distributed algorithms that maximize compute utilization and push the boundaries of training efficiency for state-of-the-art AI models. Your work will be critical to unlocking the full potential of our hardware and accelerating the pace of AI innovation.\nResponsibilities\n\n - Develop design specifications for new machine learning and linear algebra kernels and mapping to the Cerebras WSE System using various parallel programming algorithms.\n\n - Develop and debug kernel library of highly optimized low level assembly instruction and C-like domain specific language routines to implement algorithms targeting the Cerebras hardware system.\n\n - Develop and debug high-performance kernel routines in low-level assembly and a custom C-like (CSL) language, implementing algorithms optimized for the Cerebras hardware system.\n\n - Using mathematical models and analysis to measure the software performance and inform design decisions.\n\n - Develop and integrate unit and system testing methodologies to verify correct functionality and performance of kernel libraries.\n\n - Study emerging trends in Machine Learning applications and help evolve Kernel library architecture to address computational challenges of the start-of-the-art Neural Networks.\n\n - Interact with chip and system architects to optimize instruction sets, microarchitecture, and IO of next generation systems.\n\nSkills And Qualifications\n\n - Bachelor’s, Master’s, PhD or foreign equivalents in Computer Science, Computer Engineering, Mathematics, or related fields.\n\n - Understanding of hardware architecture concepts — must be comfortable learning the details of a new hardware architecture.\n\n - Skilled in C++ and Python programming languages.\n\n - Good knowledge of library and/or API development best practices.\n\n - Strong debugging skills and knowledge of debugging complex software stack.\n\nPreferred Skills And Qualifications\n\n - Experience in kernel development and/or testing.\n\n - Familiarity with parallel algorithms and distributed memory systems.\n\n - Experience in programming accelerators such as GPUs and FPGAs.\n\n - Familiarity with Machine Learning neural networks and frameworks such as TensorFlow and PyTorch.\n\n - Familiarity with HPC kernels and their optimization.\n\n \n \n\n \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"90879967-1071-4d05-9180-6e18023ed887","title":"AI Inference Core - Software Integration Engineer","department":"Software Engineering ","team":"Inference Core","employmentType":"FullTime","location":"United States and Canada","secondaryLocations":[],"publishedAt":"2026-02-05T16:10:29.592+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":null,"jobUrl":"https://jobs.ashbyhq.com/cerebras/90879967-1071-4d05-9180-6e18023ed887","applyUrl":"https://jobs.ashbyhq.com/cerebras/90879967-1071-4d05-9180-6e18023ed887/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
We are looking for a Software Integration Ninja to join the AI Inference Core team at Cerebras. This team sits at the intersection of AI infrastructure, distributed systems, compilers, runtimes, kernels, and hardware/software co-design.
The Innovation Engine for Inference Core — turning ideas into reality.
You will help take ambitious ideas from concept to working reality across the Cerebras inference stack. You will integrate and validate cross-component projects of high complexity, often on accelerated timelines, and work directly with engineers across AI, runtime, compiler, kernel, systems, and hardware teams.
Zero-to-one mission: Take incomplete ideas and early prototypes all the way to working, validated capabilities.
Cross-stack complexity: Move across AI frameworks, runtime, compiler, kernels, distributed systems, infrastructure, and hardware—not just one component or codebase.
Accelerated and dynamic cadence: Expect focused daily syncs, rapidly changing priorities, and periods of intense integration work. This is not a role for engineers seeking strictly regular, predictable work hours.
Comfortable on the hot seat: Take ownership when the path is unclear, make sound decisions with incomplete information, and stay effective when timelines are tight.
Bias for action: At critical moments, the mindset is “No Process, No Documentation, Just Get Stuff Done!!!” Cut through unnecessary ceremony, deliver the result, and then turn what you learned into better automation, diagnostics, documentation, and repeatable practices.
Team multiplier: Always push the work forward while raising the pace, clarity, and effectiveness of the people around you. We want people who bring the team with them—not lone heroes.
We prefer candidates with experience in software/hardware co-design or other complex systems, but that experience is not required. We welcome exceptional junior engineers who are eager to learn, do not shy away from ambiguity or hard work, and can demonstrate strong fundamentals, curiosity, ownership, and persistence.
Turn new inference ideas and features into integrated, working capabilities across the Cerebras platform.
Take high-value projects from zero to one—from an incomplete idea or prototype to a working, validated capability.
Integrate and validate software components spanning AI frameworks, runtime, compiler, kernels, distributed systems, and hardware.
Drive cross-component projects of high complexity from problem definition through integration, validation, and release readiness.
Collaborate closely with software and hardware engineers to make co-design trade-offs and resolve system-level issues.
Investigate and debug difficult failures across large-scale AI workloads, distributed software, infrastructure, and hardware boundaries.
Work effectively on accelerated timelines while keeping technical risks, dependencies, and decisions visible.
Participate in focused daily syncs, manage rapidly changing priorities, and drive ambiguous situations toward concrete outcomes.
Identify bottlenecks, failure modes, edge cases, and integration gaps that affect inference correctness, performance, or delivery.
Capture the essential lessons from urgent work so the next integration is faster and less chaotic.
Create momentum beyond your own work by helping teammates move faster, make better decisions, and close difficult problems together.
Strong software-engineering fundamentals and programming ability in Python, C++, Go, or a similar language.
Demonstrated ability to break down ambiguous technical problems, form hypotheses, gather evidence, and drive issues to resolution.
Experience—through professional work, internships, research, academic projects, open source, or equivalent hands-on work—building or debugging software systems.
Curiosity about how complex systems behave across component boundaries.
Willingness to read unfamiliar code, learn new layers of the stack, and take ownership beyond a narrowly defined area.
Ability to work hard and stay effective during periods of uncertainty, rapid change, and accelerated delivery.
Clear communication and strong collaboration across disciplines and levels of experience.
Experience in a startup or similarly fast-moving, resource-constrained engineering environment.
Demonstrated experience taking a project from zero to one: turning an ambiguous problem, early idea, or prototype into a working and reliable capability.
Experience with software/hardware co-design, hardware accelerators, compilers, kernels, runtimes, or low-level systems.
Experience debugging complex systems, distributed software environments, or large-scale compute clusters.
Experience with AI infrastructure, model deployment, LLMs, or multimodal workloads.
Exposure to performance debugging, profiling, observability, or failure analysis.
Familiarity with microservices, containers, cluster orchestration, cloud infrastructure, or high-performance computing.
Track record of driving cross-team projects from an incomplete idea to a reliable working result.
This role follows a hybrid schedule and requires in-office presence three days per week. Fully remote work is not available.
Office locations: Sunnyvale, CA or Toronto, ON.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n\nABOUT THE ROLE\n\nWe are looking for a Software Integration Ninja to join the AI Inference Core team at Cerebras. This team sits at the intersection of AI infrastructure, distributed systems, compilers, runtimes, kernels, and hardware/software co-design.\n\n\n\nThe Innovation Engine for Inference Core — turning ideas into reality.\n\nYou will help take ambitious ideas from concept to working reality across the Cerebras inference stack. You will integrate and validate cross-component projects of high complexity, often on accelerated timelines, and work directly with engineers across AI, runtime, compiler, kernel, systems, and hardware teams.\n\n\n\n\nA SPECIAL TASK FORCE, NOT A TYPICAL ENGINEERING ROLE\n\n - Zero-to-one mission: Take incomplete ideas and early prototypes all the way to working, validated capabilities.\n\n - Cross-stack complexity: Move across AI frameworks, runtime, compiler, kernels, distributed systems, infrastructure, and hardware—not just one component or codebase.\n\n - Accelerated and dynamic cadence: Expect focused daily syncs, rapidly changing priorities, and periods of intense integration work. This is not a role for engineers seeking strictly regular, predictable work hours.\n\n - Comfortable on the hot seat: Take ownership when the path is unclear, make sound decisions with incomplete information, and stay effective when timelines are tight.\n\n - Bias for action: At critical moments, the mindset is “No Process, No Documentation, Just Get Stuff Done!!!” Cut through unnecessary ceremony, deliver the result, and then turn what you learned into better automation, diagnostics, documentation, and repeatable practices.\n\n - Team multiplier: Always push the work forward while raising the pace, clarity, and effectiveness of the people around you. We want people who bring the team with them—not lone heroes.\n\nWe prefer candidates with experience in software/hardware co-design or other complex systems, but that experience is not required. We welcome exceptional junior engineers who are eager to learn, do not shy away from ambiguity or hard work, and can demonstrate strong fundamentals, curiosity, ownership, and persistence.\n\n\nWHAT YOU WILL DO\n\n - Turn new inference ideas and features into integrated, working capabilities across the Cerebras platform.\n\n - Take high-value projects from zero to one—from an incomplete idea or prototype to a working, validated capability.\n\n - Integrate and validate software components spanning AI frameworks, runtime, compiler, kernels, distributed systems, and hardware.\n\n - Drive cross-component projects of high complexity from problem definition through integration, validation, and release readiness.\n\n - Collaborate closely with software and hardware engineers to make co-design trade-offs and resolve system-level issues.\n\n - Investigate and debug difficult failures across large-scale AI workloads, distributed software, infrastructure, and hardware boundaries.\n\n - Work effectively on accelerated timelines while keeping technical risks, dependencies, and decisions visible.\n\n - Participate in focused daily syncs, manage rapidly changing priorities, and drive ambiguous situations toward concrete outcomes.\n\n - Identify bottlenecks, failure modes, edge cases, and integration gaps that affect inference correctness, performance, or delivery.\n\n - Capture the essential lessons from urgent work so the next integration is faster and less chaotic.\n\n - Create momentum beyond your own work by helping teammates move faster, make better decisions, and close difficult problems together.\n\n\nMINIMUM SKILLS & QUALIFICATIONS\n\n - Strong software-engineering fundamentals and programming ability in Python, C++, Go, or a similar language.\n\n - Demonstrated ability to break down ambiguous technical problems, form hypotheses, gather evidence, and drive issues to resolution.\n\n - Experience—through professional work, internships, research, academic projects, open source, or equivalent hands-on work—building or debugging software systems.\n\n - Curiosity about how complex systems behave across component boundaries.\n\n - Willingness to read unfamiliar code, learn new layers of the stack, and take ownership beyond a narrowly defined area.\n\n - Ability to work hard and stay effective during periods of uncertainty, rapid change, and accelerated delivery.\n\n - Clear communication and strong collaboration across disciplines and levels of experience.\n\n\nPREFERRED SKILLS\n\n - Experience in a startup or similarly fast-moving, resource-constrained engineering environment.\n\n - Demonstrated experience taking a project from zero to one: turning an ambiguous problem, early idea, or prototype into a working and reliable capability.\n\n - Experience with software/hardware co-design, hardware accelerators, compilers, kernels, runtimes, or low-level systems.\n\n - Experience debugging complex systems, distributed software environments, or large-scale compute clusters.\n\n - Experience with AI infrastructure, model deployment, LLMs, or multimodal workloads.\n\n - Exposure to performance debugging, profiling, observability, or failure analysis.\n\n - Familiarity with microservices, containers, cluster orchestration, cloud infrastructure, or high-performance computing.\n\n - Track record of driving cross-team projects from an incomplete idea to a reliable working result.\n\n\nLOCATION\n\n - This role follows a hybrid schedule and requires in-office presence three days per week. Fully remote work is not available.\n\n - Office locations: Sunnyvale, CA or Toronto, ON.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"98ccea5d-d67a-4b58-a44a-168eb5012fe6","title":"AI Infrastructure Operations Engineer","department":"Datacenters","team":"Datacenters","employmentType":"FullTime","location":"United States and Canada","secondaryLocations":[],"publishedAt":"2026-02-09T21:36:36.241+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":null,"jobUrl":"https://jobs.ashbyhq.com/cerebras/98ccea5d-d67a-4b58-a44a-168eb5012fe6","applyUrl":"https://jobs.ashbyhq.com/cerebras/98ccea5d-d67a-4b58-a44a-168eb5012fe6/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
The AI Infrastructure Operations Engineer (SiteOps) is an entry-level individual contributor role focused on the deployment, bring-up, monitoring, and first-line troubleshooting of Cerebras AI infrastructure in data center environments. The role supports CS systems, cluster server hardware, cluster networking hardware, and hardware telemetry and monitoring tools.
Support reliable operation and scale-out of Cerebras AI clusters by executing defined hardware bring-up and validation procedures, monitoring telemetry, performing first-line troubleshooting, and escalating issues using established workflows.
Responsibilities
Assist with deployment and bring-up of CS-X systems, cluster servers, and networking hardware;
• Execute power-on sequencing, readiness checks, and validation tests.
• Monitor hardware telemetry, alerts, and dashboards.
• Perform first-line troubleshooting and structured escalation.
• Collect logs, telemetry, and observations during incidents.
Incident Support & Tooling
Participate in incident response under senior engineer guidance;
• Use existing monitoring, telemetry, and incident tracking tools.
• Provide feedback on tooling and process gaps.
Learning & Development
Build working knowledge of Cerebras system architecture;
• Learn cluster hardware and networking fundamentals.
• Shadow senior engineers during complex debugging.
• Progress toward independent ownership of defined workflows.
Explicit Non-Responsibilities
No people management;
• No final escalation authority.
• No ownership of cluster architecture, hardware design, or tooling architecture.
Required Qualifications
Bachelor’s degree in a relevant engineering field or equivalent experience; 0–3 years experience in hardware operations, systems engineering, or datacenter environments; basic familiarity with server hardware, networking fundamentals, and Linux systems.
Preferred Qualifications
Internship or early-career experience in datacenter or hardware lab environments; exposure to monitoring or telemetry systems; comfort working in data centers.
What Success Looks Like
Consistent and correct execution of hardware bring-up procedures, early identification and escalation of issues, improving documentation quality, and clear progression toward more independent operational responsibility.
Career Path
This role progresses naturally toward Senior and Principal IC roles within AI Infrastructure Operations (SiteOps), with an optional management track.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nThe AI Infrastructure Operations Engineer (SiteOps) is an entry-level individual contributor role focused on the deployment, bring-up, monitoring, and first-line troubleshooting of Cerebras AI infrastructure in data center environments. The role supports CS systems, cluster server hardware, cluster networking hardware, and hardware telemetry and monitoring tools.\n\nSupport reliable operation and scale-out of Cerebras AI clusters by executing defined hardware bring-up and validation procedures, monitoring telemetry, performing first-line troubleshooting, and escalating issues using established workflows.\n\nResponsibilities\n\n - Assist with deployment and bring-up of CS-X systems, cluster servers, and networking hardware;\n • Execute power-on sequencing, readiness checks, and validation tests.\n • Monitor hardware telemetry, alerts, and dashboards.\n • Perform first-line troubleshooting and structured escalation.\n • Collect logs, telemetry, and observations during incidents.\n\nIncident Support & Tooling\n\n - Participate in incident response under senior engineer guidance;\n • Use existing monitoring, telemetry, and incident tracking tools.\n • Provide feedback on tooling and process gaps.\n\nLearning & Development\n\n - Build working knowledge of Cerebras system architecture;\n • Learn cluster hardware and networking fundamentals.\n • Shadow senior engineers during complex debugging.\n • Progress toward independent ownership of defined workflows.\n\nExplicit Non-Responsibilities\n\n - No people management;\n • No final escalation authority.\n • No ownership of cluster architecture, hardware design, or tooling architecture.\n\nRequired Qualifications\n\nBachelor’s degree in a relevant engineering field or equivalent experience; 0–3 years experience in hardware operations, systems engineering, or datacenter environments; basic familiarity with server hardware, networking fundamentals, and Linux systems.\n\nPreferred Qualifications\n\nInternship or early-career experience in datacenter or hardware lab environments; exposure to monitoring or telemetry systems; comfort working in data centers.\n\nWhat Success Looks Like\n\nConsistent and correct execution of hardware bring-up procedures, early identification and escalation of issues, improving documentation quality, and clear progression toward more independent operational responsibility.\n\nCareer Path\n\nThis role progresses naturally toward Senior and Principal IC roles within AI Infrastructure Operations (SiteOps), with an optional management track.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"92939082-317e-41ac-aa98-29dcf9eb5422","title":"Manufacturing Bring-up Engineer L2 ","department":"Hardware","team":"Manufacturing","employmentType":"FullTime","location":"Bengaluru, IND","secondaryLocations":[],"publishedAt":"2026-03-02T22:13:28.678+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"Karnataka","addressCountry":"India","addressLocality":"Bengaluru"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/92939082-317e-41ac-aa98-29dcf9eb5422","applyUrl":"https://jobs.ashbyhq.com/cerebras/92939082-317e-41ac-aa98-29dcf9eb5422/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
We are seeking a highly skilled and motivated Manufacturing Bring-up Engineer to join our team. As the Manufacturing Bring-up Engineer you will support our system level bring-up process execution, implementation, and evolution in the manufacturing pipeline. This is a high visibility role that requires strong technical expertise, coordination, and collaboration to deliver our product from manufacturing to the customer.
Responsibilities
Support the Cerebras manufacturing bring-up process execution to configure, test, and validate system performance prior to customer shipment
Collaborate cross-functionally with Asic, SW, Diagnostics, and QA teams to further automate and streamline the workflow for optimal manufacturing efficiency
Troubleshoot and resolve technical issues during system bring-up across Asic, SW, and QA domains
Design and implement efficient processes to manage and track system bring-up status and progress
Track and report on critical bring-up metrics to drive continuous improvement
Implement further SW automation and efficiencies to effectively scale the manufacturing bring-up process in support of the manufacturing roadmap
Skills & Qualifications
BS or MS in EE, ECE, CS or equivalent work experience
3+ years of industry experience in an operations environment
Experience in hardware bring-up and the debug of complex systems
Working knowledge and experience in Asic bringup and test processes
Working knowledge of scripting in languages such as Python and/or Perl
Proven experience in system bring-up and validation of complex computer systems or equivalent technologies
Understanding of computer system architecture and hardware components
Proficiency in scripting and automation tools for system bringup
Excellent problem-solving and communication skills with the ability to work collaboratively in a fast-paced environment
Very strong coordination and collaboration skills to manage a business-critical workflow directly in support of customer demand
Preferred:
Familiarity in creating test and s/w infrastructure at large scale
Working across global time zones
Location
Bangalore, India/Toronto, Canada/ Sunnyvale, California.
The base salary range for this position is $170,000 to $230,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role \n\nWe are seeking a highly skilled and motivated Manufacturing Bring-up Engineer to join our team. As the Manufacturing Bring-up Engineer you will support our system level bring-up process execution, implementation, and evolution in the manufacturing pipeline. This is a high visibility role that requires strong technical expertise, coordination, and collaboration to deliver our product from manufacturing to the customer. \n\nResponsibilities \n\n - Support the Cerebras manufacturing bring-up process execution to configure, test, and validate system performance prior to customer shipment \n\n - Collaborate cross-functionally with Asic, SW, Diagnostics, and QA teams to further automate and streamline the workflow for optimal manufacturing efficiency \n\n - Troubleshoot and resolve technical issues during system bring-up across Asic, SW, and QA domains \n\n - Design and implement efficient processes to manage and track system bring-up status and progress \n\n - Track and report on critical bring-up metrics to drive continuous improvement \n\n - Implement further SW automation and efficiencies to effectively scale the manufacturing bring-up process in support of the manufacturing roadmap \n\n \n\nSkills & Qualifications \n\n - BS or MS in EE, ECE, CS or equivalent work experience \n\n - 3+ years of industry experience in an operations environment \n\n - Experience in hardware bring-up and the debug of complex systems \n\n - Working knowledge and experience in Asic bringup and test processes \n\n - Working knowledge of scripting in languages such as Python and/or Perl \n\n - Proven experience in system bring-up and validation of complex computer systems or equivalent technologies \n\n - Understanding of computer system architecture and hardware components \n\n - Proficiency in scripting and automation tools for system bringup \n\n - Excellent problem-solving and communication skills with the ability to work collaboratively in a fast-paced environment \n\n - Very strong coordination and collaboration skills to manage a business-critical workflow directly in support of customer demand \n\nPreferred: \n\n - Familiarity in creating test and s/w infrastructure at large scale \n\n - Working across global time zones \n\nLocation \n\nBangalore, India/Toronto, Canada/ Sunnyvale, California.\n\nThe base salary range for this position is $170,000 to $230,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"0471b24c-013d-4e9c-a1dd-b11beadb95c7","title":"ML Software Tool Development Engineer","department":"Software Engineering ","team":"Inference Core","employmentType":"FullTime","location":"United States and Canada","secondaryLocations":[],"publishedAt":"2026-02-17T15:40:18.389+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":null,"jobUrl":"https://jobs.ashbyhq.com/cerebras/0471b24c-013d-4e9c-a1dd-b11beadb95c7","applyUrl":"https://jobs.ashbyhq.com/cerebras/0471b24c-013d-4e9c-a1dd-b11beadb95c7/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Responsibilities:
Lead the design and implementation of system-level debugging, validation, and observability platforms.
Develop automated systems for collecting and analyzing numerical, and execution anomalies.
Create visualization and analysis tools to enable efficient root-cause investigation.
Build frameworks for failure classification, regression detection, and anomaly monitoring.
Extend compilers, runtimes, and programming interfaces to support advanced profiling and instrumentation.
Improve system bring-up, low-level debug, and validation workflows.
Partner cross-functionally with compiler, hardware, firmware, runtime, and infrastructure teams.
Establish best practices for debuggability, reliability, and operational excellence.
Lead high-impact initiatives.
Support incident response and drive long-term corrective actions.
Skills & Qualifications
Strong proficiency in C++ and Python, with a track record of building reliable, high-performance systems and tooling.
Demonstrated experience debugging complex hardware/software systems and driving issues to root cause.
Experience analyzing system-level data structures, execution graphs, or dependency networks for diagnostics and validation.
Proven ability to design and build intuitive visualization and analysis tools for complex technical data.
Experience with compiler internals, custom hardware interfaces, or low-level protocol design.
Strong written and verbal communication skills, with the ability to explain technical concepts to diverse stakeholders.
Ability to work independently and lead complex technical projects end-to-end.
Preferred Skills & Qualifications
Familiarity with machine learning training and inference pipelines, especially distributed training and large-model scaling.
Prior work on high-performance clusters, HPC systems, or custom hardware/software co-design.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nResponsibilities:\n\n - Lead the design and implementation of system-level debugging, validation, and observability platforms.\n\n - Develop automated systems for collecting and analyzing numerical, and execution anomalies.\n\n - Create visualization and analysis tools to enable efficient root-cause investigation.\n\n - Build frameworks for failure classification, regression detection, and anomaly monitoring.\n\n - Extend compilers, runtimes, and programming interfaces to support advanced profiling and instrumentation.\n\n - Improve system bring-up, low-level debug, and validation workflows.\n\n - Partner cross-functionally with compiler, hardware, firmware, runtime, and infrastructure teams.\n\n - Establish best practices for debuggability, reliability, and operational excellence.\n\n - Lead high-impact initiatives.\n\n - Support incident response and drive long-term corrective actions.\n\n Skills & Qualifications\n\n - Strong proficiency in C++ and Python, with a track record of building reliable, high-performance systems and tooling.\n\n - Demonstrated experience debugging complex hardware/software systems and driving issues to root cause.\n\n - Experience analyzing system-level data structures, execution graphs, or dependency networks for diagnostics and validation.\n\n - Proven ability to design and build intuitive visualization and analysis tools for complex technical data.\n\n - Experience with compiler internals, custom hardware interfaces, or low-level protocol design.\n\n - Strong written and verbal communication skills, with the ability to explain technical concepts to diverse stakeholders.\n\n - Ability to work independently and lead complex technical projects end-to-end.\n\nPreferred Skills & Qualifications\n\n - Familiarity with machine learning training and inference pipelines, especially distributed training and large-model scaling.\n\n - Prior work on high-performance clusters, HPC systems, or custom hardware/software co-design.\n\n \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"9f6c08a7-66c5-4b54-9951-07b2d33b3beb","title":"Compute Server Platform Architect","department":"Software Engineering ","team":"Cluster","employmentType":"FullTime","location":"United States and Canada","secondaryLocations":[],"publishedAt":"2026-02-18T16:45:40.943+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":null,"jobUrl":"https://jobs.ashbyhq.com/cerebras/9f6c08a7-66c5-4b54-9951-07b2d33b3beb","applyUrl":"https://jobs.ashbyhq.com/cerebras/9f6c08a7-66c5-4b54-9951-07b2d33b3beb/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
As a Compute / Server Platform Architect on the Cluster Architecture Team, you will own the server-side platform architecture that enables Cerebras CS3-based AI clusters (training and inference) to deliver predictable performance, scalability, and reliability. Our accelerators are network-attached, so the x86 server fleet is a first-class part of the end-to-end system: it runs critical-path runtime functions (for example orchestration, prompt caching, and IO/control services) and must be co-designed with software for token-level latency, throughput, and cost efficiency. You will translate workload behavior into CPU, memory, IO, PCIe, and host-networking requirements, drive platform evaluations with vendors, and provide technical leadership through qualification and production adoption in close partnership with other function leaders and TPMs.
Responsibilities
Own the architecture for all server roles in Cerebras clusters, including definitions of server types, configurations, and lifecycle strategy.
Define and maintain server formulas (counts and ratios per CS-3 count, cluster size, and workload type) including capacity planning and headroom policy.
Specify platform configurations: CPU SKU and core strategy, our vendor roadmap (e.g., AMD, Intel, ARM), memory topology (channels, DIMM type, capacity), PCIe topology and lane budgeting, NIC selection/placement, and local NVMe policy where applicable.
Translate software and runtime flows into measurable hardware requirements (CPU utilization, memory bandwidth/latency, bursty IO patterns, queueing and concurrency limits) and communicate clear guardrails back to software teams.
Develop performance and scaling models; validate with microbenchmarks and workload-level experiments; identify bottlenecks and drive cross-stack fixes.
Define the OS, BIOS, firmware, and driver baseline for each server type; there are other teams that follow these recommendations and apply them on our fleet.
Stay current on emerging server technologies (CPU generations, new memory technologies, CXL, NVMe evolutions, SmartNIC/DPU capabilities where relevant) and run proof-of-concept evaluations to determine when to adopt.
Lead technical vendor engagements (OEM/ODM and component vendors): influence roadmap, request platform knobs, and drive joint debugging on performance or reliability issues.
Define qualification and acceptance criteria (performance, stability, operability) and partner with the Infrastructure Hardware TPM to execute qualification plans and land changes cleanly into production.
Support bring-up and rare deployment debugging in lab and staging environments; drive root-cause analysis for regressions spanning firmware, drivers, OS, and runtime behavior.
Skills and Qualifications
PhD. in Computer Science or Electrical/Computer Engineering and + 8 years industry experience, or Master’s/Bachelor’s in CS or EE + 10 years industry experience.
5+ years of experience in server platform architecture, systems performance engineering, or large-scale infrastructure design for AI/ML, HPC, or performance-sensitive distributed systems.
Deep understanding of x86 server architecture: CPU microarchitecture basics, cache hierarchies, NUMA, memory controllers/channels, and memory bandwidth vs latency tradeoffs.
Strong Linux systems knowledge: profiling and performance analysis, scheduling and syscall overheads, memory management behavior, and practical tuning methodology.
Experience reasoning about high-performance IO paths, including NIC behavior at a systems level, RDMA/RoCE concepts, and NVMe performance characteristics.
Proven ability to create capacity and performance models and validate them empirically with a rigorous benchmarking plan.
Experience working directly with vendors/partners to evaluate platforms, drive issue resolution, and influence roadmaps.
Strong cross-functional communication skills and ability to drive technical decisions through clear tradeoff documents and reviews.
Familiarity with application and system software (C, C++, Python).
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nAs a Compute / Server Platform Architect on the Cluster Architecture Team, you will own the server-side platform architecture that enables Cerebras CS3-based AI clusters (training and inference) to deliver predictable performance, scalability, and reliability. Our accelerators are network-attached, so the x86 server fleet is a first-class part of the end-to-end system: it runs critical-path runtime functions (for example orchestration, prompt caching, and IO/control services) and must be co-designed with software for token-level latency, throughput, and cost efficiency. You will translate workload behavior into CPU, memory, IO, PCIe, and host-networking requirements, drive platform evaluations with vendors, and provide technical leadership through qualification and production adoption in close partnership with other function leaders and TPMs.\n\n \n\nResponsibilities\n\n - Own the architecture for all server roles in Cerebras clusters, including definitions of server types, configurations, and lifecycle strategy.\n\n - Define and maintain server formulas (counts and ratios per CS-3 count, cluster size, and workload type) including capacity planning and headroom policy.\n\n - Specify platform configurations: CPU SKU and core strategy, our vendor roadmap (e.g., AMD, Intel, ARM), memory topology (channels, DIMM type, capacity), PCIe topology and lane budgeting, NIC selection/placement, and local NVMe policy where applicable.\n\n - Translate software and runtime flows into measurable hardware requirements (CPU utilization, memory bandwidth/latency, bursty IO patterns, queueing and concurrency limits) and communicate clear guardrails back to software teams.\n\n - Develop performance and scaling models; validate with microbenchmarks and workload-level experiments; identify bottlenecks and drive cross-stack fixes.\n\n - Define the OS, BIOS, firmware, and driver baseline for each server type; there are other teams that follow these recommendations and apply them on our fleet.\n\n - Stay current on emerging server technologies (CPU generations, new memory technologies, CXL, NVMe evolutions, SmartNIC/DPU capabilities where relevant) and run proof-of-concept evaluations to determine when to adopt.\n\n - Lead technical vendor engagements (OEM/ODM and component vendors): influence roadmap, request platform knobs, and drive joint debugging on performance or reliability issues.\n\n - Define qualification and acceptance criteria (performance, stability, operability) and partner with the Infrastructure Hardware TPM to execute qualification plans and land changes cleanly into production.\n\n - Support bring-up and rare deployment debugging in lab and staging environments; drive root-cause analysis for regressions spanning firmware, drivers, OS, and runtime behavior.\n\nSkills and Qualifications\n\n - PhD. in Computer Science or Electrical/Computer Engineering and + 8 years industry experience, or Master’s/Bachelor’s in CS or EE + 10 years industry experience.\n\n - 5+ years of experience in server platform architecture, systems performance engineering, or large-scale infrastructure design for AI/ML, HPC, or performance-sensitive distributed systems.\n\n - Deep understanding of x86 server architecture: CPU microarchitecture basics, cache hierarchies, NUMA, memory controllers/channels, and memory bandwidth vs latency tradeoffs.\n\n - Strong Linux systems knowledge: profiling and performance analysis, scheduling and syscall overheads, memory management behavior, and practical tuning methodology.\n\n - Experience reasoning about high-performance IO paths, including NIC behavior at a systems level, RDMA/RoCE concepts, and NVMe performance characteristics.\n\n - Proven ability to create capacity and performance models and validate them empirically with a rigorous benchmarking plan.\n\n - Experience working directly with vendors/partners to evaluate platforms, drive issue resolution, and influence roadmaps.\n\n - Strong cross-functional communication skills and ability to drive technical decisions through clear tradeoff documents and reviews.\n\n - Familiarity with application and system software (C, C++, Python).\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"d654a704-2c58-4ba6-9109-2c92aecb2503","title":"Applied Machine Learning Research Scientist","department":"Software Engineering ","team":"Cluster","employmentType":"FullTime","location":"United States and Canada","secondaryLocations":[],"publishedAt":"2026-03-05T22:03:05.014+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":null,"jobUrl":"https://jobs.ashbyhq.com/cerebras/d654a704-2c58-4ba6-9109-2c92aecb2503","applyUrl":"https://jobs.ashbyhq.com/cerebras/d654a704-2c58-4ba6-9109-2c92aecb2503/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
As an Applied Machine Learning Research Scientist at Cerebras, you will play a key role in turning modern machine learning techniques into scalable, high-performance systems. This role sits at the intersection of modeling and systems focused not on publishing new algorithms, but on understanding how they work and making them run effectively at scale. Your work will directly impact how large language models (LLMs) are trained, optimized, and deployed on one of the most advanced AI platforms in the world.
You will work closely with researchers and senior engineers to implement and improve workflows for LLM pretraining, fine-tuning, and reinforcement learning-based post-training. This includes building training pipelines, debugging complex system behaviors, improving model quality, and iterating on data and evaluation strategies. Your contributions will help translate cutting-edge ML ideas into reliable, production-ready systems that solve real-world problems.
This role is ideal for candidates who enjoy hands-on engineering, want to build deep intuition for ML systems, and are excited about working on LLMs and reinforcement learning in practice, not just in theory.
Responsibilities
Apply post-training techniques (e.g. RLVR, RLHF, GRPO etc.) techniques to improve model performance.
Build and maintain evaluation pipelines to measure model performance across tasks and domains.
Debug issues across the ML stack, including data pipelines, training jobs, model outputs and mixed or lower precision computation.
Collaborate with researchers to translate ML ideas into efficient, scalable implementation.
Design, implement, and scale ML pipelines across all stages of LLM development (pretraining, fine-tuning, alignment).
Work with large datasets, including dataset generation, filtering, and synthetic data approaches.
Optimize training and inference workflows for performance, efficiency, and reliability.
Contribute high-quality, maintainable code to shared ML infrastructure.
Skills & Qualifications
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
4+ years of experience (including internships, research, or industry experience) working with machine learning systems; we are hiring multiple positions for various levels.
Strong programming skills in Python.
Experience with ML frameworks such as PyTorch.
Solid understanding of machine learning fundamentals.
Familiarity with deep learning architectures, particularly transformers.
Ability to read and understand modern ML papers and implement key ideas.
Preferred Skills & Qualifications
Experience working with large language models (training, fine-tuning, and evaluation).
Familiarity with reinforcement learning concepts.
Experience with distributed training frameworks (e.g., FSDP, Megatron).
Experience working with large-scale datasets and data pipelines.
Experience debugging or optimizing ML systems for performance.
• Contributions to meaningful codebases, projects, or open-source systems
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nAs an Applied Machine Learning Research Scientist at Cerebras, you will play a key role in turning modern machine learning techniques into scalable, high-performance systems. This role sits at the intersection of modeling and systems focused not on publishing new algorithms, but on understanding how they work and making them run effectively at scale. Your work will directly impact how large language models (LLMs) are trained, optimized, and deployed on one of the most advanced AI platforms in the world. \n\nYou will work closely with researchers and senior engineers to implement and improve workflows for LLM pretraining, fine-tuning, and reinforcement learning-based post-training. This includes building training pipelines, debugging complex system behaviors, improving model quality, and iterating on data and evaluation strategies. Your contributions will help translate cutting-edge ML ideas into reliable, production-ready systems that solve real-world problems. \n\nThis role is ideal for candidates who enjoy hands-on engineering, want to build deep intuition for ML systems, and are excited about working on LLMs and reinforcement learning in practice, not just in theory. \n\nResponsibilities \n\n - Apply post-training techniques (e.g. RLVR, RLHF, GRPO etc.) techniques to improve model performance.\n\n - Build and maintain evaluation pipelines to measure model performance across tasks and domains.\n\n - Debug issues across the ML stack, including data pipelines, training jobs, model outputs and mixed or lower precision computation.\n\n - Collaborate with researchers to translate ML ideas into efficient, scalable implementation.\n\n - Design, implement, and scale ML pipelines across all stages of LLM development (pretraining, fine-tuning, alignment).\n\n - Work with large datasets, including dataset generation, filtering, and synthetic data approaches.\n\n - Optimize training and inference workflows for performance, efficiency, and reliability.\n\n - Contribute high-quality, maintainable code to shared ML infrastructure. \n\nSkills & Qualifications \n\n - Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.\n\n - 4+ years of experience (including internships, research, or industry experience) working with machine learning systems; we are hiring multiple positions for various levels. \n\n - Strong programming skills in Python.\n\n - Experience with ML frameworks such as PyTorch.\n\n - Solid understanding of machine learning fundamentals.\n\n - Familiarity with deep learning architectures, particularly transformers.\n\n - Ability to read and understand modern ML papers and implement key ideas.\n\nPreferred Skills & Qualifications \n\n - Experience working with large language models (training, fine-tuning, and evaluation).\n\n - Familiarity with reinforcement learning concepts.\n\n - Experience with distributed training frameworks (e.g., FSDP, Megatron).\n\n - Experience working with large-scale datasets and data pipelines.\n\n - Experience debugging or optimizing ML systems for performance.\n • Contributions to meaningful codebases, projects, or open-source systems \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"d418c1b5-1968-452b-89d0-4d3fa566265e","title":"Physical Design Engineer (Bengaluru)","department":"Hardware","team":"Silicon","employmentType":"FullTime","location":"Bengaluru, IND","secondaryLocations":[],"publishedAt":"2026-05-06T02:25:08.663+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"Karnataka","addressCountry":"India","addressLocality":"Bengaluru"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/d418c1b5-1968-452b-89d0-4d3fa566265e","applyUrl":"https://jobs.ashbyhq.com/cerebras/d418c1b5-1968-452b-89d0-4d3fa566265e/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
As our team grows Cerebras is looking for a world class physical design engineer. We are looking for a strong learner who can learn how we do PD and integration of our wafer scale design.
As a member of our tight knit physical design team, you will perform a variety of physical design tasks such as synthesis, place and route, timing and block closure / sign off. You will be involved in all aspects of physical design and implementation. You will work closely with the RTL team and with full-chip integration of these blocks.
Skills and Qualifications:
7+ years of physical design/verification experience.
Strong experience in block/subsystem timing closure.
Strong ability to learn and grow with the team.
Strong knowledge of block level and full-chip physical verification methodology.
Expert at optimizing for the best power/performance and area.
Experience with block physical design, PDV and IR.
Expert with ICV or Calibre tools resolving block and full-chip DRC and LVS issues.
Expert with IR/EM analysis and resolution.
Good understanding of full chip floor-planning and integration.
Strong ability in scripting languages like Tcl and Python. Ability to make flow enhancements.
Demonstrated ability to work with RTL teams to optimize for physical design.
Ability to take on a leadership role after ramping up on wafer scale design.
Should demonstrate learn and be curious, good fundamental understanding of PD concepts and should be coachable.
BSEE, MSEE, PH.D EE preferred.
Preferred:
Experience with the complete physical design flow. Knowledge of Synopsys tool suite is a plus.
Synthesis and STA would be good to have.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nAs our team grows Cerebras is looking for a world class physical design engineer. We are looking for a strong learner who can learn how we do PD and integration of our wafer scale design.\nAs a member of our tight knit physical design team, you will perform a variety of physical design tasks such as synthesis, place and route, timing and block closure / sign off. You will be involved in all aspects of physical design and implementation. You will work closely with the RTL team and with full-chip integration of these blocks.\n\nSkills and Qualifications:\n\n - 7+ years of physical design/verification experience.\n\n - Strong experience in block/subsystem timing closure.\n\n - Strong ability to learn and grow with the team.\n\n - Strong knowledge of block level and full-chip physical verification methodology.\n\n - Expert at optimizing for the best power/performance and area.\n\n - Experience with block physical design, PDV and IR.\n\n - Expert with ICV or Calibre tools resolving block and full-chip DRC and LVS issues.\n\n - Expert with IR/EM analysis and resolution.\n\n - Good understanding of full chip floor-planning and integration.\n\n - Strong ability in scripting languages like Tcl and Python. Ability to make flow enhancements.\n\n - Demonstrated ability to work with RTL teams to optimize for physical design.\n\n - Ability to take on a leadership role after ramping up on wafer scale design.\n\n - Should demonstrate learn and be curious, good fundamental understanding of PD concepts and should be coachable.\n\n - BSEE, MSEE, PH.D EE preferred.\n\nPreferred:\n\n - Experience with the complete physical design flow. Knowledge of Synopsys tool suite is a plus.\n\n - Synthesis and STA would be good to have.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"2c786281-e51c-4d2d-a760-2ef907d81760","title":"Director, Strategic Finance - Corporate FP&A","department":"Corporate","team":"Finance","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2026-05-21T15:19:46.206+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/2c786281-e51c-4d2d-a760-2ef907d81760","applyUrl":"https://jobs.ashbyhq.com/cerebras/2c786281-e51c-4d2d-a760-2ef907d81760/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
This role is a front-row seat in a company at the leading edge of AI compute. You will create the corporate FP&A operating system for the company: long-range planning, annual planning, forecasting, executive reporting, guidance support, and SG&A business partnering that keeps decision-ready insight flowing as the company scales. The scope can stretch for a proven FP&A leader seeking a sharper public-company platform or a high-potential leader ready to pull the function forward from day one. You will work across leadership teams and be accountable for outcomes, not outputs. You will report to the Head of FP&A.
Why now
Cerebras is newly public and scaling at pace. This commercial traction demands exceptional financial operations. This role will be a driver of this capability.
Responsibilities
Ownership: Company-wide corporate FP&A, including owning the company model, leading long-range and annual planning, monthly forecasting, revenue forecasting, G&A budgeting, headcount, spend management, Board reporting, and public-company reporting support.
Operating model: Player-coach on a flat, high-standards team. You bring a track record of building talent-dense teams, use technology to multiply output, and set the bar by staying close to the work.
Success definition: FP&A is the center of context for the organization. The team will deliver investor-grade information to the right partners at the right time.
What you will build
Corporate FP&A infrastructure for a newly public company: planning, forecasting, reporting, guidance support, and G&A spend visibility.
A decision-quality KPI and reporting architecture: scorecards, dashboards, recurring reviews, and crisp narratives that leadership and investors trust.
Financial models leaders can use: clean inputs, stress-tested assumptions, clear outputs, and documented logic across planning, budgeting, forecasts, and guidance support.
A world-class business partnership motion: business leaders rely on the FP&A team for insight. We deliver true partnership, not spreadsheet help
Make order out of chaos. Build mechanisms that turn messy business inputs into repeatable processes including forecasting cadences, metric definitions, reconciliation paths, and accountability loops.
Automation and tooling that compounds output for a small, talent-dense team, including structured data pulls, workflow automation, and pragmatic AI use.
Public-company-ready operating rhythms: clean close-to-insight timelines, clear ownership, guidance support, and durable definitions that scale with scrutiny.
What you will own
G&A business partnering: Serve as the primary finance partner to G&A leadership. Bring structure, speed, and judgment to budgeting, headcount planning, spend management, and strategic investment decisions.
Corporate planning: Own and continuously improve forecasting, budgeting, annual planning, long-range planning, scenario planning, and performance reporting across the company.
Revenue forecasting: Own the company revenue forecast and partner closely with Sales and Product to build accurate, data-driven projections, variance insights, and guidance support.
Executive, Board, and investor reporting: Prepare and deliver financial reporting, insights, and commentary for executive leadership, the Board, investors, and public-market processes.
KPIs and dashboards: Develop and refine KPIs, scorecards, dashboards, and analytical frameworks that highlight trends, track operating leverage, and guide leadership decisions.
Capital allocation and systems: Conduct analysis to support investment decisions and long-term planning, and drive improvements in financial systems, AI-enabled workflows, tools, and data quality.
What success looks like in the first 6 to 12 months
You earn the trust of leadership by delivering the right insights at the right time in the right way.
G&A leaders and executives proactively pull you into decisions because your work improves outcomes, not just visibility.
Durable insight assets are live (dashboards, forecast packs, KPI definitions, Board-ready and investor-ready reporting) with a clear cadence and single-source-of-truth inputs.
The long-range plan, annual operating plan, and monthly forecast process run smoothly, with scenario levers leadership uses for decisions, guidance support, and operating tradeoffs.
G&A spend and headcount visibility improve through better planning discipline, reducing surprises and improving decision quality.
The revenue forecast and variance process are credible, timely, and actionable, with clear ownership and repeatable guidance-support inputs.
You have improved the system: fewer manual consolidations, fewer one-off analyses, and more AI-enabled mechanisms that keep the business informed as scale increases.
What we are looking for
We are hiring for judgment, agency, systems thinking, and player-coach leadership. You know what great FP&A looks like, build what the business needs next, and bring others along.
15+ years of total experience (rough guide), ideally across corporate FP&A, strategic finance, or adjacent roles. We are open to proven Directors and VP-level leaders seeking a high-slope public-company platform.
Corporate FP&A leadership experience, ideally in a public-company or newly public environment, or training from a comparably rigorous analytical setting. You have seen excellent FP&A up close and can raise the bar quickly.
Strong financial modeling skills. You can build from scratch, pressure-test assumptions, and defend outputs with clarity.
Proven G&A and executive-facing partnership. You earn trust by being fast, right, and useful, then scale that trust through repeatable mechanisms.
Player-coach systems thinker. You have built or raised the bar for small, talent-dense teams and can build infrastructure that works as pace increases and data gets messy.
High agency. You operate in ambiguity, move without perfect inputs or direction, close loops, and bring pattern recognition rather than a rigid playbook.
Clear executive communication. You distill complexity into concise narratives, perform grounded root-cause analysis, and influence decisions.
Technical fluency beyond spreadsheets (preferred). Comfortable with Excel, PowerPoint, SQL, Python, AI tools, and planning or BI tooling.
Ways to stand out
Experience in hardware, semiconductor, infrastructure, or other complex businesses with sophisticated revenue and spend planning.
Time at a public, newly public, or high-growth company navigating rapid scale, guidance support, and public-company planning rhythms.
Experience with performance management, scorecards, dashboarding, and operating leverage analysis.
Fluency with planning, ERP, and BI systems (for example NetSuite, Oracle, or Looker) and the practical reality of integrating finance processes across functions.
Strong AI affinity: you apply modern tools to automate work, accelerate analysis, raise quality, and extend small-team output.
Location
In-person at Cerebras headquarters in Sunnyvale, California.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nThis role is a front-row seat in a company at the leading edge of AI compute. You will create the corporate FP&A operating system for the company: long-range planning, annual planning, forecasting, executive reporting, guidance support, and SG&A business partnering that keeps decision-ready insight flowing as the company scales. The scope can stretch for a proven FP&A leader seeking a sharper public-company platform or a high-potential leader ready to pull the function forward from day one. You will work across leadership teams and be accountable for outcomes, not outputs. You will report to the Head of FP&A.\n\nWhy now\n\nCerebras is newly public and scaling at pace. This commercial traction demands exceptional financial operations. This role will be a driver of this capability.\n\nResponsibilities\n\n - Ownership: Company-wide corporate FP&A, including owning the company model, leading long-range and annual planning, monthly forecasting, revenue forecasting, G&A budgeting, headcount, spend management, Board reporting, and public-company reporting support.\n\n - Operating model: Player-coach on a flat, high-standards team. You bring a track record of building talent-dense teams, use technology to multiply output, and set the bar by staying close to the work.\n\n - Success definition: FP&A is the center of context for the organization. The team will deliver investor-grade information to the right partners at the right time.\n\nWhat you will build\n\n - Corporate FP&A infrastructure for a newly public company: planning, forecasting, reporting, guidance support, and G&A spend visibility.\n\n - A decision-quality KPI and reporting architecture: scorecards, dashboards, recurring reviews, and crisp narratives that leadership and investors trust.\n\n - Financial models leaders can use: clean inputs, stress-tested assumptions, clear outputs, and documented logic across planning, budgeting, forecasts, and guidance support.\n\n - A world-class business partnership motion: business leaders rely on the FP&A team for insight. We deliver true partnership, not spreadsheet help\n\n - Make order out of chaos. Build mechanisms that turn messy business inputs into repeatable processes including forecasting cadences, metric definitions, reconciliation paths, and accountability loops.\n\n - Automation and tooling that compounds output for a small, talent-dense team, including structured data pulls, workflow automation, and pragmatic AI use.\n\n - Public-company-ready operating rhythms: clean close-to-insight timelines, clear ownership, guidance support, and durable definitions that scale with scrutiny.\n\nWhat you will own\n\n - G&A business partnering: Serve as the primary finance partner to G&A leadership. Bring structure, speed, and judgment to budgeting, headcount planning, spend management, and strategic investment decisions.\n\n - Corporate planning: Own and continuously improve forecasting, budgeting, annual planning, long-range planning, scenario planning, and performance reporting across the company.\n\n - Revenue forecasting: Own the company revenue forecast and partner closely with Sales and Product to build accurate, data-driven projections, variance insights, and guidance support.\n\n - Executive, Board, and investor reporting: Prepare and deliver financial reporting, insights, and commentary for executive leadership, the Board, investors, and public-market processes.\n\n - KPIs and dashboards: Develop and refine KPIs, scorecards, dashboards, and analytical frameworks that highlight trends, track operating leverage, and guide leadership decisions.\n\n - Capital allocation and systems: Conduct analysis to support investment decisions and long-term planning, and drive improvements in financial systems, AI-enabled workflows, tools, and data quality.\n\nWhat success looks like in the first 6 to 12 months\n\n - You earn the trust of leadership by delivering the right insights at the right time in the right way.\n\n - G&A leaders and executives proactively pull you into decisions because your work improves outcomes, not just visibility.\n\n - Durable insight assets are live (dashboards, forecast packs, KPI definitions, Board-ready and investor-ready reporting) with a clear cadence and single-source-of-truth inputs.\n\n - The long-range plan, annual operating plan, and monthly forecast process run smoothly, with scenario levers leadership uses for decisions, guidance support, and operating tradeoffs.\n\n - G&A spend and headcount visibility improve through better planning discipline, reducing surprises and improving decision quality.\n\n - The revenue forecast and variance process are credible, timely, and actionable, with clear ownership and repeatable guidance-support inputs.\n\n - You have improved the system: fewer manual consolidations, fewer one-off analyses, and more AI-enabled mechanisms that keep the business informed as scale increases.\n\nWhat we are looking for\n\nWe are hiring for judgment, agency, systems thinking, and player-coach leadership. You know what great FP&A looks like, build what the business needs next, and bring others along.\n\n - 15+ years of total experience (rough guide), ideally across corporate FP&A, strategic finance, or adjacent roles. We are open to proven Directors and VP-level leaders seeking a high-slope public-company platform.\n\n - Corporate FP&A leadership experience, ideally in a public-company or newly public environment, or training from a comparably rigorous analytical setting. You have seen excellent FP&A up close and can raise the bar quickly.\n\n - Strong financial modeling skills. You can build from scratch, pressure-test assumptions, and defend outputs with clarity.\n\n - Proven G&A and executive-facing partnership. You earn trust by being fast, right, and useful, then scale that trust through repeatable mechanisms.\n\n - Player-coach systems thinker. You have built or raised the bar for small, talent-dense teams and can build infrastructure that works as pace increases and data gets messy.\n\n - High agency. You operate in ambiguity, move without perfect inputs or direction, close loops, and bring pattern recognition rather than a rigid playbook.\n\n - Clear executive communication. You distill complexity into concise narratives, perform grounded root-cause analysis, and influence decisions.\n\n - Technical fluency beyond spreadsheets (preferred). Comfortable with Excel, PowerPoint, SQL, Python, AI tools, and planning or BI tooling.\n\nWays to stand out\n\n - Experience in hardware, semiconductor, infrastructure, or other complex businesses with sophisticated revenue and spend planning.\n\n - Time at a public, newly public, or high-growth company navigating rapid scale, guidance support, and public-company planning rhythms.\n\n - Experience with performance management, scorecards, dashboarding, and operating leverage analysis.\n\n - Fluency with planning, ERP, and BI systems (for example NetSuite, Oracle, or Looker) and the practical reality of integrating finance processes across functions.\n\n - Strong AI affinity: you apply modern tools to automate work, accelerate analysis, raise quality, and extend small-team output.\n\nLocation\n\nIn-person at Cerebras headquarters in Sunnyvale, California.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"ea0a48cf-8c1d-444c-9a69-a5e100c311e6","title":"Senior Accountant ","department":"Corporate","team":"Finance","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2026-05-26T20:33:08.186+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/ea0a48cf-8c1d-444c-9a69-a5e100c311e6","applyUrl":"https://jobs.ashbyhq.com/cerebras/ea0a48cf-8c1d-444c-9a69-a5e100c311e6/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
The Senior Operations Accountant will be a key contributor to the Finance and Operations teams, reporting to the Senior Cost Accounting Manager. This role is designed for a detail-oriented professional who excels in fast-paced environments and can derive insights from complex manufacturing and inventory data. You will support the end-to-end execution of cost accounting and fixed asset processes.
Cost Capitalization & Inventory Accounting
Execute monthly inventory reconciliations and post all related journal entries.
Perform calculations for inventory rebates, wafer manufacturing yield losses, and monthly facilities allocations.
Accrue and capitalize freight and tariff costs on a monthly basis.
Ensure proper inventory classification across Raw Materials (RM), Work-in-Process (WIP), and Finished Goods (FG).
Support the coordination of physical inventory counts with Operations and external auditors.
Fixed Assets & Capital Expenditure
Manage the end-to-end fixed asset lifecycle, including additions, disposals, and monthly depreciation runs.
Track and account for internal deployments of inventory to Property, Plant, and Equipment (PPE).
Maintain the fixed asset register, ensuring accurate classification and useful life assignments in accordance with GAAP.
Monitor Construction-in-Progress (CIP) accounts and ensure timely capitalization of completed projects.
Support the audit of fixed assets, including periodic physical tagging and verification of equipment.
Manufacturing & COGS Analysis
Analyze Finished Goods movements to ensure accurate accounting for COGS and RMAs.
Review COGS transactions for completeness and perform gross margin flux analysis.
Capitalize manufacturing overhead and operational costs to ensure accurate variance analysis.
Audit & Cross-Functional Support
Prepare schedules and provide documentation for internal and external audit requests related to inventory, cost, and fixed assets.
Partner with Supply Chain and Procurement to validate inventory movements and system accuracy.
Education: Bachelor’s degree in Accounting, Finance, or a related field.
Certification: CPA or CMA preferred, with strong knowledge of GAAP, inventory costing methodologies, and fixed asset accounting.
Experience: 4+ years of progressive accounting experience, with a focus on manufacturing, hardware, or infrastructure-intensive environments.
Systems: Strong proficiency in NetSuite and advanced Excel skills (e.g., pivot tables, VLOOKUPs, data modeling).
Attributes: Ability to work with high volumes of unstructured data and a desire to optimize processes in a high-growth environment.
Location: Sunnyvale, CA (Hybrid: 3 days per week in-office)
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n\nABOUT THE ROLE\n\nThe Senior Operations Accountant will be a key contributor to the Finance and Operations teams, reporting to the Senior Cost Accounting Manager. This role is designed for a detail-oriented professional who excels in fast-paced environments and can derive insights from complex manufacturing and inventory data. You will support the end-to-end execution of cost accounting and fixed asset processes.\n\n\nRESPONSIBILITIES\n\nCost Capitalization & Inventory Accounting\n\n - Execute monthly inventory reconciliations and post all related journal entries.\n\n - Perform calculations for inventory rebates, wafer manufacturing yield losses, and monthly facilities allocations.\n\n - Accrue and capitalize freight and tariff costs on a monthly basis.\n\n - Ensure proper inventory classification across Raw Materials (RM), Work-in-Process (WIP), and Finished Goods (FG).\n\n - Support the coordination of physical inventory counts with Operations and external auditors.\n\nFixed Assets & Capital Expenditure\n\n - Manage the end-to-end fixed asset lifecycle, including additions, disposals, and monthly depreciation runs.\n\n - Track and account for internal deployments of inventory to Property, Plant, and Equipment (PPE).\n\n - Maintain the fixed asset register, ensuring accurate classification and useful life assignments in accordance with GAAP.\n\n - Monitor Construction-in-Progress (CIP) accounts and ensure timely capitalization of completed projects.\n\n - Support the audit of fixed assets, including periodic physical tagging and verification of equipment.\n\nManufacturing & COGS Analysis\n\n - Analyze Finished Goods movements to ensure accurate accounting for COGS and RMAs.\n\n - Review COGS transactions for completeness and perform gross margin flux analysis.\n\n - Capitalize manufacturing overhead and operational costs to ensure accurate variance analysis.\n\nAudit & Cross-Functional Support\n\n - Prepare schedules and provide documentation for internal and external audit requests related to inventory, cost, and fixed assets.\n\n - Partner with Supply Chain and Procurement to validate inventory movements and system accuracy.\n\n\nQUALIFICATIONS\n\n - Education: Bachelor’s degree in Accounting, Finance, or a related field.\n\n - Certification: CPA or CMA preferred, with strong knowledge of GAAP, inventory costing methodologies, and fixed asset accounting.\n\n - Experience: 4+ years of progressive accounting experience, with a focus on manufacturing, hardware, or infrastructure-intensive environments.\n\n - Systems: Strong proficiency in NetSuite and advanced Excel skills (e.g., pivot tables, VLOOKUPs, data modeling).\n\n - Attributes: Ability to work with high volumes of unstructured data and a desire to optimize processes in a high-growth environment.\n\n\nADDITIONAL INFORMATION\n\n - Location: Sunnyvale, CA (Hybrid: 3 days per week in-office)\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"4a9ff42b-c834-4445-ba47-2f90d74d83a5","title":"Security & IT General Opportunities","department":"IT & Security","team":"Security","employmentType":"FullTime","location":"United States and Canada","secondaryLocations":[],"publishedAt":"2026-05-28T20:48:14.601+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":null,"jobUrl":"https://jobs.ashbyhq.com/cerebras/4a9ff42b-c834-4445-ba47-2f90d74d83a5","applyUrl":"https://jobs.ashbyhq.com/cerebras/4a9ff42b-c834-4445-ba47-2f90d74d83a5/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Our IT & Security team sits at the intersection of security, infrastructure, and cutting-edge AI systems. The team plays a critical role in ensuring Cerebras’ environments are secure, reliable, scalable, and ready to support customers operating at the frontier of AI.
We are looking for people who care deeply about operational excellence, security best practices, automation, and building systems that can support a rapidly growing organization.
Depending on the role and team needs, you may contribute to areas such as:
Securing and scaling enterprise IT, cloud, network, and infrastructure environments.
Building automation and tooling to improve security, reliability, and operational efficiency.
Supporting security engineering, detection, response, and vulnerability management efforts.
Improving identity, access, endpoint, network, and systems security practices.
Partnering cross-functionally with IT, Infrastructure, Security, and Engineering teams.
Developing processes and systems that help Cerebras scale securely and efficiently.
Supporting operational rigor across high-impact technical environments.
We are interested in hearing from candidates who:
Think about infrastructure, security, and operations through an automation-first mindset.
Believe that repeatable, scalable systems are better than manual processes.
Care deeply about security, reliability, and operational excellence.
Enjoy working on complex, high-impact systems.
Are comfortable collaborating across IT, Infrastructure, Security, and Engineering teams.
Want to build, improve, and protect systems that support some of the most advanced AI workloads in the world.
Relevant experience may include one or more of the following:
IT Operations or Systems Administration.
Enterprise Security.
Security Engineering.
Network Security.
Systems Security.
Infrastructure Security.
Cloud Security.
Endpoint, Identity, or Access Management.
Security Operations, Detection, or Incident Response.
Automation, scripting, or infrastructure-as-code practices.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n\nABOUT THE ROLE\n\nOur IT & Security team sits at the intersection of security, infrastructure, and cutting-edge AI systems. The team plays a critical role in ensuring Cerebras’ environments are secure, reliable, scalable, and ready to support customers operating at the frontier of AI.\n\nWe are looking for people who care deeply about operational excellence, security best practices, automation, and building systems that can support a rapidly growing organization.\n\n\n\n\nRESPONSIBILITIES\n\nDepending on the role and team needs, you may contribute to areas such as:\n\n - Securing and scaling enterprise IT, cloud, network, and infrastructure environments.\n\n - Building automation and tooling to improve security, reliability, and operational efficiency.\n\n - Supporting security engineering, detection, response, and vulnerability management efforts.\n\n - Improving identity, access, endpoint, network, and systems security practices.\n\n - Partnering cross-functionally with IT, Infrastructure, Security, and Engineering teams.\n\n - Developing processes and systems that help Cerebras scale securely and efficiently.\n\n - Supporting operational rigor across high-impact technical environments.\n\n\nSKILLS & QUALIFICATIONS\n\nWe are interested in hearing from candidates who:\n\n - Think about infrastructure, security, and operations through an automation-first mindset.\n\n - Believe that repeatable, scalable systems are better than manual processes.\n\n - Care deeply about security, reliability, and operational excellence.\n\n - Enjoy working on complex, high-impact systems.\n\n - Are comfortable collaborating across IT, Infrastructure, Security, and Engineering teams.\n\n - Want to build, improve, and protect systems that support some of the most advanced AI workloads in the world.\n\n\nPREFERRED SKILLS & QUALIFICATIONS\n\nRelevant experience may include one or more of the following:\n\n - IT Operations or Systems Administration.\n\n - Enterprise Security.\n\n - Security Engineering.\n\n - Network Security.\n\n - Systems Security.\n\n - Infrastructure Security.\n\n - Cloud Security.\n\n - Endpoint, Identity, or Access Management.\n\n - Security Operations, Detection, or Incident Response.\n\n - Automation, scripting, or infrastructure-as-code practices.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"d82f92ec-1287-469f-a5a9-2bb77e6cef2f","title":"ASIC Architect","department":"Hardware","team":"Silicon","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2026-07-10T19:52:48.544+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/d82f92ec-1287-469f-a5a9-2bb77e6cef2f","applyUrl":"https://jobs.ashbyhq.com/cerebras/d82f92ec-1287-469f-a5a9-2bb77e6cef2f/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Responsibilities
Translate high level architecture spec to micro-architecture feature requirements
Bring up new features in the performance/power model
Perform comprehensive PPA trade-offs for new architectural features
Extract insights for new features and micro-architecture power efficiency
Profile workloads, identify bottlenecks and project competition performance for benchmarking
Engage with SW teams for end-end application level modeling at cluster level
Identify kernel level HW acceleration level opportunities
Qualifications
Masters/PhD in Electrical/Computer Engineering
10+ years of experience across performance analysis and modeling across GPUs, CPUs or accelerator products
Strong background in computer architecture and key high level architectural trade-offs
Comfortable standing up new performance models from scratch in Python or similar analytical environments
Exposure to micro-code (kernel) performance bottlenecks and optimization techniques
Good understanding of how high-level workloads map to underlying micro-architecture is desired
Understanding of basic ML workload profiling techniques and model network architecture is preferred
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nResponsibilities\n\n - Translate high level architecture spec to micro-architecture feature requirements\n\n - Bring up new features in the performance/power model\n\n - Perform comprehensive PPA trade-offs for new architectural features\n\n - Extract insights for new features and micro-architecture power efficiency\n\n - Profile workloads, identify bottlenecks and project competition performance for benchmarking \n\n - Engage with SW teams for end-end application level modeling at cluster level\n\n - Identify kernel level HW acceleration level opportunities\n\nQualifications\n\n - Masters/PhD in Electrical/Computer Engineering \n\n - 10+ years of experience across performance analysis and modeling across GPUs, CPUs or accelerator products\n\n - Strong background in computer architecture and key high level architectural trade-offs\n\n - Comfortable standing up new performance models from scratch in Python or similar analytical environments\n\n - Exposure to micro-code (kernel) performance bottlenecks and optimization techniques\n\n - Good understanding of how high-level workloads map to underlying micro-architecture is desired\n\n - Understanding of basic ML workload profiling techniques and model network architecture is preferred\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"1e1e6848-b35e-465e-96b3-3cd5538cc1f1","title":"Director / Senior Director, Critical Facility Operations ","department":"Datacenters","team":"Datacenters","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2026-06-03T01:43:45.239+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/1e1e6848-b35e-465e-96b3-3cd5538cc1f1","applyUrl":"https://jobs.ashbyhq.com/cerebras/1e1e6848-b35e-465e-96b3-3cd5538cc1f1/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
At Cerebras, we build systems that redefine the scale of compute. That ambition extends beyond silicon into the infrastructure that powers it.
We are looking for a Director / Sr. Director of Critical Facility Operations to lead the environments that enable next-generation AI workloads. This leader will own availability, operational integrity, and performance across a colocation-driven data center footprint—ensuring our infrastructure operates with precision, predictability, and zero room for error.
This is not a traditional facilities role. You will operate at the intersection of mission-critical engineering, vendor orchestration, and operational excellence, building systems and teams that can scale with the most demanding compute environments in the world.
Responsibilities
Drive a no-downtime operating model across all facilities
Own uptime performance end-to-end including incident response and RCA
Build a culture where failures are analyzed and not repeated
Vendor & Colocation
Architect and run a high-discipline vendor operating model
Convert vendor relationships into measurable systems
Lead deep operational reviews and enforce accountability
Contracts
Align SLAs, incentives, and performance
Eliminate ambiguity in ownership and response
Safety
Build a zero-incident safety culture
Ensure rigor in high-risk procedures
Maintenance
Transform preventive maintenance into failure prevention
Implement predictive strategies where possible
Operations
Standardize SOPs, MOPs, and EOPs
Build a high-signal operating rhythm
Benchmark against hyperscale operators
Leadership
Build high-performing, high-agency teams
Drive ownership, speed, and technical excellence
Scaling
Ensure operational readiness for new builds
Influence design and site strategy
Skills & Qualifications
12–15+ years in mission-critical facilities or data center operations
Experience managing multi-site, vendor-heavy environments
Strong expertise in electrical and mechanical systems
Proven track record in improving uptime and performance
Success Metrics
Availability and SLA performance
Incident reduction and MTTR improvement
Vendor performance and accountability
Safety metrics
Maintenance quality and execution
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nAt Cerebras, we build systems that redefine the scale of compute. That ambition extends beyond silicon into the infrastructure that powers it.\n\nWe are looking for a Director / Sr. Director of Critical Facility Operations to lead the environments that enable next-generation AI workloads. This leader will own availability, operational integrity, and performance across a colocation-driven data center footprint—ensuring our infrastructure operates with precision, predictability, and zero room for error.\n\nThis is not a traditional facilities role. You will operate at the intersection of mission-critical engineering, vendor orchestration, and operational excellence, building systems and teams that can scale with the most demanding compute environments in the world.\n\nResponsibilities\n\n - Drive a no-downtime operating model across all facilities\n\n - Own uptime performance end-to-end including incident response and RCA\n\n - Build a culture where failures are analyzed and not repeated\n\nVendor & Colocation\n\n - Architect and run a high-discipline vendor operating model\n\n - Convert vendor relationships into measurable systems\n\n - Lead deep operational reviews and enforce accountability\n\nContracts\n\n - Align SLAs, incentives, and performance\n\n - Eliminate ambiguity in ownership and response\n\nSafety\n\n - Build a zero-incident safety culture\n\n - Ensure rigor in high-risk procedures\n\nMaintenance\n\n - Transform preventive maintenance into failure prevention\n\n - Implement predictive strategies where possible\n\nOperations\n\n - Standardize SOPs, MOPs, and EOPs\n\n - Build a high-signal operating rhythm\n\n - Benchmark against hyperscale operators\n\nLeadership\n\n - Build high-performing, high-agency teams\n\n - Drive ownership, speed, and technical excellence\n\nScaling\n\n - Ensure operational readiness for new builds\n\n - Influence design and site strategy\n\nSkills & Qualifications\n\n - 12–15+ years in mission-critical facilities or data center operations\n\n - Experience managing multi-site, vendor-heavy environments\n\n - Strong expertise in electrical and mechanical systems\n\n - Proven track record in improving uptime and performance\n\nSuccess Metrics\n\n - Availability and SLA performance\n\n - Incident reduction and MTTR improvement\n\n - Vendor performance and accountability\n\n - Safety metrics\n\n - Maintenance quality and execution\n\n \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"91fb96a9-1737-4d3d-ac73-ac2f6c40ec58","title":"Senior / Staff Technical Program Manager - Datacenter Capacity Delivery (E2E) ","department":"Datacenters","team":"Datacenters","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2026-06-03T04:40:21.041+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/91fb96a9-1737-4d3d-ac73-ac2f6c40ec58","applyUrl":"https://jobs.ashbyhq.com/cerebras/91fb96a9-1737-4d3d-ac73-ac2f6c40ec58/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
The DC Delivery E2E TPM is the single-threaded owner for delivering data center capacity from forecast → site strategy → design → construction → infrastructure readiness → go-live.
You will operate as the SSOT (Single Source of Truth) for delivery milestones, risks, and capacity outcomes while orchestrating cross-functional execution across internal teams and external partners. This is a frontier-scale role where ambiguity is high, timelines are compressed, and stakes are critical to company growth.
Responsibilities
End-to-End Capacity Delivery
Own delivery of AI-optimized data center capacity (colo, build-to-suit, retrofits, and owned facilities) from pre-contract planning through operational readiness.
Deliver MW-scale infrastructure aligned to aggressive GPU/AI system deployment targets.
Drive clarity from ambiguity—translate high-level demand signals into executable delivery programs.
Program Structuring & Execution
Decompose complex build programs into workstreams with clear owners, milestones, and deliverables.
Build integrated plans spanning real estate, power/energy, design, procurement, construction, and deployment.
Establish critical path visibility and aggressively manage schedule compression.
Cross-Functional Leadership
Orchestrate execution across:
Real estate & site selection
Power & energy strategy (utilities, PPAs, interconnects)
Data center design (MEP, liquid cooling, high-density racks)
Supply chain & long-lead equipment procurement
Construction & commissioning
Infrastructure deployment (rack/cluster install)
Networking & backbone connectivity
Security, compliance, and operations readiness
Act as the primary interface with colocation providers, EPCs, utilities, and key vendors.
Risk, Cost & Governance
Identify and drive resolution of critical risks, constraints, and blockers across power, equipment, permitting, and supply chain.
Own and maintain program budgets, CapEx forecasts, and capital allocation narratives.
Provide structured updates and escalation paths to executive leadership.
Demand & Capacity Planning Integration
Partner with capacity planning, AI infrastructure, and finance teams to translate model demand into site-level capacity strategies.
Align build plans with power availability, network topology, and hardware rollout schedules.
Continuously optimize for time-to-capacity and cost-per-MW / cost-per-GPU deployed.
Operational Excellence
Drive E2E improvements in delivery through:
Standardization of build and commissioning processes
Implementation of program tooling and dashboards
Post-mortems and lessons learned loops
Establish scalable mechanisms to support rapid global expansion.
Communication & Leadership
Serve as SSOT for program health, milestones, and risks.
Deliver concise, high-signal updates to senior executives.
Operate effectively across distributed teams with up to 50% travel.
Skills & Qualifications
12-15+ years in mission-critical facilities or data center operations
Experience managing multi-site, vendor-heavy environments
Strong expertise in electrical and mechanical systems
Proven track record in improving uptime and performance
Preferred Qualifications
Experience at hyperscalers (Google, Meta, Microsoft) or neo-cloud / AI infra companies (CoreWeave, Lambda, etc.).
Familiarity with high-density AI workloads (liquid cooling, >30kW racks, GPU clusters).
Experience with:
Utility engagement and power delivery constraints
Long-lead supply chain planning (transformers, switchgear, chillers)
Commissioning and data center handover processes
Ability to operate in high-growth, ambiguous environments with limited structure.
Strong executive presence and ability to influence without authority.
What sets you apart
Extreme ownership mindset — you treat capacity delivery as a personal SLA.
Ability to move fast without breaking systems, balancing urgency with rigor.
Comfort operating at the intersection of hardware, real estate, and software scaling demands.
Clear, structured communicator who can turn chaos into executable plans.
Bias for action with a track record of delivering results under pressure.
Location: US (preferred SF Bay Area / remote with travel)
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nThe DC Delivery E2E TPM is the single-threaded owner for delivering data center capacity from forecast → site strategy → design → construction → infrastructure readiness → go-live.\n\nYou will operate as the SSOT (Single Source of Truth) for delivery milestones, risks, and capacity outcomes while orchestrating cross-functional execution across internal teams and external partners. This is a frontier-scale role where ambiguity is high, timelines are compressed, and stakes are critical to company growth.\n\nResponsibilities\n\nEnd-to-End Capacity Delivery\n\n - Own delivery of AI-optimized data center capacity (colo, build-to-suit, retrofits, and owned facilities) from pre-contract planning through operational readiness.\n\n - Deliver MW-scale infrastructure aligned to aggressive GPU/AI system deployment targets.\n\n - Drive clarity from ambiguity—translate high-level demand signals into executable delivery programs.\n\nProgram Structuring & Execution\n\n - Decompose complex build programs into workstreams with clear owners, milestones, and deliverables.\n\n - Build integrated plans spanning real estate, power/energy, design, procurement, construction, and deployment.\n\n - Establish critical path visibility and aggressively manage schedule compression.\n\nCross-Functional Leadership\n\n - Orchestrate execution across:\n \n - Real estate & site selection\n \n - Power & energy strategy (utilities, PPAs, interconnects)\n \n - Data center design (MEP, liquid cooling, high-density racks)\n \n - Supply chain & long-lead equipment procurement\n \n - Construction & commissioning\n \n - Infrastructure deployment (rack/cluster install)\n \n - Networking & backbone connectivity\n \n - Security, compliance, and operations readiness\n\n - Act as the primary interface with colocation providers, EPCs, utilities, and key vendors.\n\nRisk, Cost & Governance\n\n - Identify and drive resolution of critical risks, constraints, and blockers across power, equipment, permitting, and supply chain.\n\n - Own and maintain program budgets, CapEx forecasts, and capital allocation narratives.\n\n - Provide structured updates and escalation paths to executive leadership.\n\nDemand & Capacity Planning Integration\n\n - Partner with capacity planning, AI infrastructure, and finance teams to translate model demand into site-level capacity strategies.\n\n - Align build plans with power availability, network topology, and hardware rollout schedules.\n\n - Continuously optimize for time-to-capacity and cost-per-MW / cost-per-GPU deployed.\n\nOperational Excellence\n\n - Drive E2E improvements in delivery through:\n \n - Standardization of build and commissioning processes\n \n - Implementation of program tooling and dashboards\n \n - Post-mortems and lessons learned loops\n\n - Establish scalable mechanisms to support rapid global expansion.\n\nCommunication & Leadership\n\n - Serve as SSOT for program health, milestones, and risks.\n\n - Deliver concise, high-signal updates to senior executives.\n\n - Operate effectively across distributed teams with up to 50% travel.\n\nSkills & Qualifications\n\n - 12-15+ years in mission-critical facilities or data center operations\n\n - Experience managing multi-site, vendor-heavy environments\n\n - Strong expertise in electrical and mechanical systems\n\n - Proven track record in improving uptime and performance\n\nPreferred Qualifications \n\n - Experience at hyperscalers (Google, Meta, Microsoft) or neo-cloud / AI infra companies (CoreWeave, Lambda, etc.).\n\n - Familiarity with high-density AI workloads (liquid cooling, >30kW racks, GPU clusters).\n\n - Experience with:\n \n - Utility engagement and power delivery constraints\n \n - Long-lead supply chain planning (transformers, switchgear, chillers)\n \n - Commissioning and data center handover processes\n\n - Ability to operate in high-growth, ambiguous environments with limited structure.\n\n - Strong executive presence and ability to influence without authority.\n\nWhat sets you apart \n\n - Extreme ownership mindset — you treat capacity delivery as a personal SLA.\n\n - Ability to move fast without breaking systems, balancing urgency with rigor.\n\n - Comfort operating at the intersection of hardware, real estate, and software scaling demands.\n\n - Clear, structured communicator who can turn chaos into executable plans.\n\n - Bias for action with a track record of delivering results under pressure.\n\nLocation: US (preferred SF Bay Area / remote with travel)\n\n \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"024f1401-76cc-43fa-9338-cc3262a793d3","title":"System Software Engineer (Embedded)","department":"Hardware","team":"Systems","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2026-02-17T20:54:33.551+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/024f1401-76cc-43fa-9338-cc3262a793d3","applyUrl":"https://jobs.ashbyhq.com/cerebras/024f1401-76cc-43fa-9338-cc3262a793d3/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
As part of the Embedded Software team, you will help build the critical software foundation that powers the Cerebras Wafer Scale Engine (WSE)—the world’s largest AI processor. Our team owns a diverse range of embedded and system level components that enable the WSE to operate reliably at scale, including microcontroller firmware, wafer level monitoring logic, system administration services, and the Linux platform and BSP layers that keep the entire system running smoothly.
This role exists at the intersection of embedded systems, platform engineering, and distributed system enablement. As our technology and deployments continue to scale, we are expanding the team with versatile engineers eager to work across multiple layers of the software stack. You will help build administrative services that connect the WSE’s system software to cluster-level orchestration, collaborate closely with hardware and ASIC teams, and contribute to the robustness, visibility, and operability of our next-generation AI systems.
Responsibilities
Develop administrative software that enables communication between system-level software and cluster-level control layers.
Provide and extend Linux BSP support, ensuring reliability and maintainability of system level platform components.
Collaborate across teams to gather requirements, define scope, plan milestones, and deliver high-quality implementations.
Work closely with datacenter operations and debug teams to diagnose system level issues, root cause failures, and implement fixes.
Partner with hardware and ASIC teams to design and implement software that monitors system hardware and wafer level behavior.
Contribute to improving system reliability, observability, and long-term maintainability across layers of the embedded stack.
Participate in code reviews, design discussions, and cross-team technical planning.
Skills & Qualifications
Minimum Qualifications
Bachelor’s degree in computer engineering, Electrical Engineering, Computer Science, or related field.
5+ years of experience in building production-quality software in C++ or Golang.
Solid understanding of embedded systems fundamentals or system hardware interactions.
Experience working in cross-functional engineering environments.
Preferred Qualifications
Master’s degree in computer engineering, Electrical Engineering, Computer Science, or related field.
Exposure to distributed systems, cluster-level orchestration, or datacenter environments.
Familiarity with Linux kernel concepts, device drivers, or BSP layers.
Experience debugging hardware/software interactions using tools such as logic analyzers, JTAG, or profiling/tracing frameworks.
Experience contributing to system monitoring, observability tooling, or hardware level telemetry pipelines.
Experience working on server hardware, AI accelerators, hardware accelerator, datacenter, AI Hardware, enterprise product, GPU, CPU, TPU, server platform etc.
The base salary range for this position is $175,000 to $275,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role \n\nAs part of the Embedded Software team, you will help build the critical software foundation that powers the Cerebras Wafer Scale Engine (WSE)—the world’s largest AI processor. Our team owns a diverse range of embedded and system level components that enable the WSE to operate reliably at scale, including microcontroller firmware, wafer level monitoring logic, system administration services, and the Linux platform and BSP layers that keep the entire system running smoothly. \n\nThis role exists at the intersection of embedded systems, platform engineering, and distributed system enablement. As our technology and deployments continue to scale, we are expanding the team with versatile engineers eager to work across multiple layers of the software stack. You will help build administrative services that connect the WSE’s system software to cluster-level orchestration, collaborate closely with hardware and ASIC teams, and contribute to the robustness, visibility, and operability of our next-generation AI systems. \n\nResponsibilities \n\n - Develop administrative software that enables communication between system-level software and cluster-level control layers. \n\n - Provide and extend Linux BSP support, ensuring reliability and maintainability of system level platform components. \n\n - Collaborate across teams to gather requirements, define scope, plan milestones, and deliver high-quality implementations. \n\n - Work closely with datacenter operations and debug teams to diagnose system level issues, root cause failures, and implement fixes. \n\n - Partner with hardware and ASIC teams to design and implement software that monitors system hardware and wafer level behavior. \n\n - Contribute to improving system reliability, observability, and long-term maintainability across layers of the embedded stack. \n\n - Participate in code reviews, design discussions, and cross-team technical planning. \n\nSkills & Qualifications \n\nMinimum Qualifications \n\n - Bachelor’s degree in computer engineering, Electrical Engineering, Computer Science, or related field. \n\n - 5+ years of experience in building production-quality software in C++ or Golang. \n\n - Solid understanding of embedded systems fundamentals or system hardware interactions. \n\n - Experience working in cross-functional engineering environments. \n\nPreferred Qualifications \n\n - Master’s degree in computer engineering, Electrical Engineering, Computer Science, or related field. \n\n - Exposure to distributed systems, cluster-level orchestration, or datacenter environments. \n\n - Familiarity with Linux kernel concepts, device drivers, or BSP layers. \n\n - Experience debugging hardware/software interactions using tools such as logic analyzers, JTAG, or profiling/tracing frameworks. \n\n - Experience contributing to system monitoring, observability tooling, or hardware level telemetry pipelines. \n\n - Experience working on server hardware, AI accelerators, hardware accelerator, datacenter, AI Hardware, enterprise product, GPU, CPU, TPU, server platform etc.\n\nThe base salary range for this position is $175,000 to $275,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"2a133db0-a8bf-4945-8320-e5aff8d333cc","title":"IT SRE Team Lead","department":"IT & Security","team":"IT","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2026-04-09T00:41:09.734+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/2a133db0-a8bf-4945-8320-e5aff8d333cc","applyUrl":"https://jobs.ashbyhq.com/cerebras/2a133db0-a8bf-4945-8320-e5aff8d333cc/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
We are seeking an experienced IT SRE Team Lead to build and run the reliability function for Cerebras' internal technology estate.
The IT SRE Team Lead will be responsible for the availability, performance, and operational quality of the systems Cerebras employees rely on every day, including identity, endpoint management, collaboration, SaaS, and internal networking. The right candidate will bring a software engineering mindset to IT operations, treating corporate infrastructure as code, with measurable SLOs, automated remediation, and a ruthless focus on eliminating toil.
You will build and lead a small, high-leverage team of engineers who build tooling, write automation, and respond when things break. You will partner closely with the security, networking, and infrastructure teams to make sure the internal environment stays fast, stable, and secure as the company scales.
Responsibilities
Define and own the reliability strategy for internal IT systems, including SLOs, error budgets, and operational health reporting.
Build and lead a team of IT SRE engineers focused on automation, observability, and incident response for corporate systems.
Design and implement automation to eliminate manual IT work across provisioning, access management, patching, and lifecycle operations.
Instrument internal services and SaaS integrations with monitoring, alerting, and on-call workflows.
Run incident response for IT outages, including root cause analysis and durable remediation.
Drive infrastructure-as-code and GitOps practices across IT-owned systems.
Partner with security and networking teams on identity, access, and network reliability.
Skills And Qualifications
Minimum 8 years of experience in SRE, DevOps, or IT engineering roles, with at least 2 years in a leadership capacity.
Direct hands on experience with AI coding tools, building and deploying AI agents for triage and bug fixes.
Strong software engineering background with hands-on experience in Python, Go, or similar, and comfort writing production-grade automation.
Deep experience with identity platforms (Okta, Entra), endpoint management (Jamf, Intune), and SaaS integration patterns.
Hands-on experience with infrastructure-as-code tools (Terraform) and CI/CD pipelines applied to IT systems.
Proven track record of running on-call rotations, defining SLOs, and driving operational maturity in a fast-moving environment.
Experience supporting highly technical engineering populations where uptime and speed both matter.
Strong organizational skills with the ability to multitask and prioritize.
Detail-oriented with the ability to anticipate the needs of customers and internal stakeholders.
Proactive, adaptable, and able to thrive in a rapidly changing environment.
Excellent verbal and written communication skills.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nWe are seeking an experienced IT SRE Team Lead to build and run the reliability function for Cerebras' internal technology estate. \n\nThe IT SRE Team Lead will be responsible for the availability, performance, and operational quality of the systems Cerebras employees rely on every day, including identity, endpoint management, collaboration, SaaS, and internal networking. The right candidate will bring a software engineering mindset to IT operations, treating corporate infrastructure as code, with measurable SLOs, automated remediation, and a ruthless focus on eliminating toil. \n\nYou will build and lead a small, high-leverage team of engineers who build tooling, write automation, and respond when things break. You will partner closely with the security, networking, and infrastructure teams to make sure the internal environment stays fast, stable, and secure as the company scales. \n\nResponsibilities \n\n - Define and own the reliability strategy for internal IT systems, including SLOs, error budgets, and operational health reporting. \n\n - Build and lead a team of IT SRE engineers focused on automation, observability, and incident response for corporate systems. \n\n - Design and implement automation to eliminate manual IT work across provisioning, access management, patching, and lifecycle operations. \n\n - Instrument internal services and SaaS integrations with monitoring, alerting, and on-call workflows. \n\n - Run incident response for IT outages, including root cause analysis and durable remediation. \n\n - Drive infrastructure-as-code and GitOps practices across IT-owned systems. \n\n - Partner with security and networking teams on identity, access, and network reliability. \n\nSkills And Qualifications \n\n - Minimum 8 years of experience in SRE, DevOps, or IT engineering roles, with at least 2 years in a leadership capacity. \n\n - Direct hands on experience with AI coding tools, building and deploying AI agents for triage and bug fixes. \n\n - Strong software engineering background with hands-on experience in Python, Go, or similar, and comfort writing production-grade automation. \n\n - Deep experience with identity platforms (Okta, Entra), endpoint management (Jamf, Intune), and SaaS integration patterns. \n\n - Hands-on experience with infrastructure-as-code tools (Terraform) and CI/CD pipelines applied to IT systems. \n\n - Proven track record of running on-call rotations, defining SLOs, and driving operational maturity in a fast-moving environment. \n\n - Experience supporting highly technical engineering populations where uptime and speed both matter. \n\n - Strong organizational skills with the ability to multitask and prioritize. \n\n - Detail-oriented with the ability to anticipate the needs of customers and internal stakeholders. \n\n - Proactive, adaptable, and able to thrive in a rapidly changing environment. \n\n - Excellent verbal and written communication skills. \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"0322249e-e2d4-4e0a-9133-6f173000173a","title":"Manufacturing Linux Network Engineer","department":"IT & Security","team":"IT","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2026-05-01T16:11:29.007+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/0322249e-e2d4-4e0a-9133-6f173000173a","applyUrl":"https://jobs.ashbyhq.com/cerebras/0322249e-e2d4-4e0a-9133-6f173000173a/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
We are seeking an experienced Manufacturing Linux / Network Engineer to design, implement, and maintain robust IT and network infrastructure across our manufacturing facilities. The ideal candidate brings deep expertise in Linux systems administration (Red Hat / Rocky Linux), network security (Palo Alto firewalls), storage infrastructure, CI/CD pipelines (Jenkins), and infrastructure automation (Ansible). This role sits at the intersection of enterprise IT and plant-floor operations, and is critical to delivering the high availability, security, and performance that modern manufacturing environments demand.
Design, deploy, and maintain LAN/WAN network infrastructure spanning manufacturing plants, warehouses, cloud providers, and corporate sites.
Implement and manage high-speed core switching at 10G and 100G using Arista, Juniper, and other enterprise switching platforms; ensure scalable, resilient fabric design.
Configure, troubleshoot, and optimize Layer 2/3 networking (LACP, VLANs, BGP) and security controls (Palo Alto firewalls, VPNs, NAC, IDS/IPS); manage ISP link failover and path redundancy.
Deploy, configure, and maintain Linux servers (Red Hat / Rocky Linux) using automation tools including Ansible, MAAS, Foreman, and custom scripting to ensure consistent, repeatable provisioning.
Monitor network and system performance — uptime, latency, bandwidth utilization, and capacity — across all sites; proactively detect and resolve issues before they impact
Design and maintain redundancy, failover, QoS, and traffic engineering strategies to support 24/7 manufacturing operations and minimize unplanned downtime.
Manage structured cabling, Wi-Fi 6/6E wireless infrastructure, and ruggedized networking hardware suited for plant-floor environments.
Partner with engineering, automation, OT, and IT security teams to ensure secure and reliable connectivity for production and operational systems.
Lead and contribute to greenfield and brownfield IT/OT modernization projects, including network redesigns for new equipment rollouts and facility expansions.
Own network documentation including topology diagrams, IP address management (IPAM), and standard operating procedures; keep them current as infrastructure evolves.
Provide Tier 2/3 support for network and Linux system incidents at manufacturing sites; participate in on-call rotation for production-critical issues.
Bachelor’s degree in Computer Science, Information Technology, Electrical Engineering, or a related field.
4+ years of experience in network and Linux infrastructure engineering, preferably in a manufacturing or industrial environment.
Deep Linux expertise with Rocky Linux / RHEL, including administration of core infrastructure services: DNS, DHCP, and network storage (NFS).
Hands-on experience with Palo Alto Networks firewalls, including policy management, threat prevention, and configuration of active/standby ISP failover links.
Demonstrated ability to automate infrastructure at scale; proven track record applying Infrastructure as Code (IaC) best practices using Ansible, Terraform, or equivalent tooling.
Strong knowledge of networking fundamentals: TCP/IP, VLANs, routing protocols (OSPF, BGP), switching, and network security.
Experience with enterprise network vendors including Cisco, Arista, and Juniper; familiarity with ruggedized industrial switches (Hirschmann, Cisco IE series, or similar).
Knowledge of cybersecurity best practices aligned with NIST frameworks.
Experience with wireless networking (Wi-Fi 6, cellular/private LTE) in industrial or plant-floor settings.
Experience with network monitoring and observability platforms (Grafana, Zabbix, or similar) and on-call alerting integrations such as PagerDuty.
Ability to review data center and plant-floor physical designs; experience collaborating with cabling vendors and server rack build teams to implement structured cabling best practices.
Comfortable working on the plant floor alongside cross-functional teams including maintenance, engineering, and operations.
Strong troubleshooting, documentation, and communication skills.
Able to participate in on-call rotation and respond to after-hours production-critical incidents.
Experience with Python scripting for network automation, configuration management, and compliance reporting.
Experience with cloud connectivity and hybrid network architectures (AWS, Azure, or GCP) in manufacturing contexts.
Familiarity with MES platforms and their integration with enterprise IT systems.
Knowledge of structured cabling standards (TIA-568, IEC 11801) and data center operations within manufacturing environments.
Experience with SD-WAN solutions for multi-site manufacturing connectivity.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n\nABOUT THE ROLE\n\nWe are seeking an experienced Manufacturing Linux / Network Engineer to design, implement, and maintain robust IT and network infrastructure across our manufacturing facilities. The ideal candidate brings deep expertise in Linux systems administration (Red Hat / Rocky Linux), network security (Palo Alto firewalls), storage infrastructure, CI/CD pipelines (Jenkins), and infrastructure automation (Ansible). This role sits at the intersection of enterprise IT and plant-floor operations, and is critical to delivering the high availability, security, and performance that modern manufacturing environments demand.\n\n\nRESPONSIBILITIES\n\n - Design, deploy, and maintain LAN/WAN network infrastructure spanning manufacturing plants, warehouses, cloud providers, and corporate sites.\n\n - Implement and manage high-speed core switching at 10G and 100G using Arista, Juniper, and other enterprise switching platforms; ensure scalable, resilient fabric design.\n\n - Configure, troubleshoot, and optimize Layer 2/3 networking (LACP, VLANs, BGP) and security controls (Palo Alto firewalls, VPNs, NAC, IDS/IPS); manage ISP link failover and path redundancy.\n\n - Deploy, configure, and maintain Linux servers (Red Hat / Rocky Linux) using automation tools including Ansible, MAAS, Foreman, and custom scripting to ensure consistent, repeatable provisioning.\n\n - Monitor network and system performance — uptime, latency, bandwidth utilization, and capacity — across all sites; proactively detect and resolve issues before they impact\n\n - Design and maintain redundancy, failover, QoS, and traffic engineering strategies to support 24/7 manufacturing operations and minimize unplanned downtime.\n\n - Manage structured cabling, Wi-Fi 6/6E wireless infrastructure, and ruggedized networking hardware suited for plant-floor environments.\n\n - Partner with engineering, automation, OT, and IT security teams to ensure secure and reliable connectivity for production and operational systems.\n\n - Lead and contribute to greenfield and brownfield IT/OT modernization projects, including network redesigns for new equipment rollouts and facility expansions.\n\n - Own network documentation including topology diagrams, IP address management (IPAM), and standard operating procedures; keep them current as infrastructure evolves.\n\n - Provide Tier 2/3 support for network and Linux system incidents at manufacturing sites; participate in on-call rotation for production-critical issues.\n\n\nREQUIREMENTS\n\n - Bachelor’s degree in Computer Science, Information Technology, Electrical Engineering, or a related field.\n\n - 4+ years of experience in network and Linux infrastructure engineering, preferably in a manufacturing or industrial environment.\n\n - Deep Linux expertise with Rocky Linux / RHEL, including administration of core infrastructure services: DNS, DHCP, and network storage (NFS).\n\n - Hands-on experience with Palo Alto Networks firewalls, including policy management, threat prevention, and configuration of active/standby ISP failover links.\n\n - Demonstrated ability to automate infrastructure at scale; proven track record applying Infrastructure as Code (IaC) best practices using Ansible, Terraform, or equivalent tooling. \n\n - Strong knowledge of networking fundamentals: TCP/IP, VLANs, routing protocols (OSPF, BGP), switching, and network security.\n\n - Experience with enterprise network vendors including Cisco, Arista, and Juniper; familiarity with ruggedized industrial switches (Hirschmann, Cisco IE series, or similar).\n\n - Knowledge of cybersecurity best practices aligned with NIST frameworks. \n\n - Experience with wireless networking (Wi-Fi 6, cellular/private LTE) in industrial or plant-floor settings. \n\n - Experience with network monitoring and observability platforms (Grafana, Zabbix, or similar) and on-call alerting integrations such as PagerDuty.\n\n - Ability to review data center and plant-floor physical designs; experience collaborating with cabling vendors and server rack build teams to implement structured cabling best practices.\n\n - Comfortable working on the plant floor alongside cross-functional teams including maintenance, engineering, and operations.\n\n - Strong troubleshooting, documentation, and communication skills. \n\n - Able to participate in on-call rotation and respond to after-hours production-critical incidents. \n\n\nPREFERRED QUALIFICATIONS\n\n - Experience with Python scripting for network automation, configuration management, and compliance reporting.\n\n - Experience with cloud connectivity and hybrid network architectures (AWS, Azure, or GCP) in manufacturing contexts.\n\n - Familiarity with MES platforms and their integration with enterprise IT systems. \n\n - Knowledge of structured cabling standards (TIA-568, IEC 11801) and data center operations within manufacturing environments.\n\n - Experience with SD-WAN solutions for multi-site manufacturing connectivity. \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"6d966c0a-d587-4a16-bf57-cfb4b4eb7eef","title":"Senior Engineer: Post Silicon - Bring Up ","department":"Hardware","team":"Silicon","employmentType":"FullTime","location":"Bengaluru, IND","secondaryLocations":[],"publishedAt":"2026-02-16T22:19:16.198+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"Karnataka","addressCountry":"India","addressLocality":"Bengaluru"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/6d966c0a-d587-4a16-bf57-cfb4b4eb7eef","applyUrl":"https://jobs.ashbyhq.com/cerebras/6d966c0a-d587-4a16-bf57-cfb4b4eb7eef/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
In this exciting role, you will be responsible for bring up and optimizations of Cerebras’s Wafer Scale Engine (WSE). Suitable candidate will have experience delivering end to end solutions working closely with teams across chip design, system performance, software development and productization.
Responsibilities:
On Wafer Scale Engines, develop and debug flows that embed well tested and deployable optimizations in production processes to reduce time and costs
Work on refining AI Systems across H/W-S/W design constraints such as di/dt, V-F characterization space, current and temperature limits in relation to optimizations for performance.
Develop/Enhance infrastructure to enable silicon for real world workload testing
Develop self-checking metrics, as well as instrumentation for debug and coverage
Work with the silicon architects/designers, performance engineers and software engineers to enhance performance of Wafer Scale Engines.
Work across domains such as, Software, Design, Verification, Emulation & Validation to refine and optimize performance and process.
Work with CI/CD tools, git repositories, github, git actions/Jenkins, merge and release flows to streamline test and release.
Skills & Qualifications:
BS/BE/B.Tech or MS/M.Tech in EE, ECE, CS or equivalent work experience
7-10+ years of industry experience
3-5 years of experience in Pre-silicon & Post Silicon ASIC hardware
Good understanding of computer architecture and networking
Excellent Coding in languages such as Python/Verilog/System Verilog and C
Proficient in hardware/software codesign and layered architectures.
Excellent debugging, analytical, and problem-solving skills
Proficient in large scale testing and automation using pytest and python
Good presentation skills to refine diverse information and put forth optimization strategies and results.
Good interpersonal skills, ability & desire to work as a standout colleague
Proven track record of working cross-functionally learning fast and driving issues to closure
Preferred:
Previous work in AI-ML with 100+ CPU core & communication fabric-based design.
Familiarity with in-line testing and diagnostics using CPU memory and execution with self-checking.
Knowledge of chip defect profiles and mitigation strategies across the hardware and software stack
Familiarity in creating test and s/w infrastructure at large scale
Working across global time zones
Location:
Bangalore, India
Toronto, Canada
Sunnyvale, California.
For Sunnyvale: The base salary range for this position is $175,000 to $275,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\nIn this exciting role, you will be responsible for bring up and optimizations of Cerebras’s Wafer Scale Engine (WSE). Suitable candidate will have experience delivering end to end solutions working closely with teams across chip design, system performance, software development and productization.\n\n\nResponsibilities:\n\n - On Wafer Scale Engines, develop and debug flows that embed well tested and deployable optimizations in production processes to reduce time and costs \n\n - Work on refining AI Systems across H/W-S/W design constraints such as di/dt, V-F characterization space, current and temperature limits in relation to optimizations for performance.\n\n - Develop/Enhance infrastructure to enable silicon for real world workload testing\n\n - Develop self-checking metrics, as well as instrumentation for debug and coverage\n\n - Work with the silicon architects/designers, performance engineers and software engineers to enhance performance of Wafer Scale Engines.\n\n - Work across domains such as, Software, Design, Verification, Emulation & Validation to refine and optimize performance and process.\n\n - Work with CI/CD tools, git repositories, github, git actions/Jenkins, merge and release flows to streamline test and release.\n\nSkills & Qualifications:\n\n - BS/BE/B.Tech or MS/M.Tech in EE, ECE, CS or equivalent work experience\n\n - 7-10+ years of industry experience\n\n - 3-5 years of experience in Pre-silicon & Post Silicon ASIC hardware\n\n - Good understanding of computer architecture and networking\n\n - Excellent Coding in languages such as Python/Verilog/System Verilog and C\n\n - Proficient in hardware/software codesign and layered architectures.\n\n - Excellent debugging, analytical, and problem-solving skills\n\n - Proficient in large scale testing and automation using pytest and python\n\n - Good presentation skills to refine diverse information and put forth optimization strategies and results.\n\n - Good interpersonal skills, ability & desire to work as a standout colleague\n\n - Proven track record of working cross-functionally learning fast and driving issues to closure \n\nPreferred:\n\n - Previous work in AI-ML with 100+ CPU core & communication fabric-based design.\n\n - Familiarity with in-line testing and diagnostics using CPU memory and execution with self-checking.\n\n - Knowledge of chip defect profiles and mitigation strategies across the hardware and software stack\n\n - Familiarity in creating test and s/w infrastructure at large scale\n\n - Working across global time zones \n\nLocation:\nBangalore, India\n\nToronto, Canada\n\nSunnyvale, California.\n\n \n\nFor Sunnyvale: The base salary range for this position is $175,000 to $275,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"4dd7ad78-80c1-4826-ac4c-8f0371773281","title":"Senior Staff Electrical Engineer","department":"Hardware","team":"Systems","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2026-02-19T01:59:58.158+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/4dd7ad78-80c1-4826-ac4c-8f0371773281","applyUrl":"https://jobs.ashbyhq.com/cerebras/4dd7ad78-80c1-4826-ac4c-8f0371773281/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Cerebras is seeking an exceptional Senior Staff Electrical Engineer to drive our system hardware development. This role is focusing on defining and driving system architecture and strategy for high-performance compute, AI/ML accelerators and advanced ASIC platforms.
Responsibilities
Lead system architecture and hardware design from concept to production release.
Own hardware development, system specification, schematic and layout design, bring up, debug, validation and system integration.
Drive future technology development with internal and industry partners.
Collaborate with various design and operations teams: manufacturing operations & test engineering, supply chain, ASIC, mechanical, signal integrity, power delivery, layout, embedded & diagnostic, etc.
Minimum Qualifications
B.S.c, M.S.c, or Ph.D. degree in electrical engineering, or equivalent experience.
Minimum 10 years of experience as a board design engineer (exceptional candidates with other experience levels will also be considered).
Experience with system design, digital circuits, power delivery, voltage regulators, and high-speed signal integrity.
System-level understanding and familiarity with production environment.
Proficiency with lab/test scripting SW (e.g., Python).
Personal skills: self-instruction, multi-disciplined, multi-tasking and good interpersonal relationship.
Experience working on server hardware, AI accelerators, hardware accelerator, datacenter, AI Hardware, enterprise product, GPU, CPU, TPU, server platform etc.
Preferred Qualifications
Demonstrated expertise in enterprise and data center products.
Solid background in execution from concept, bring up, development and product launch end-to-end product development cycle.
Deep technical knowledge of system hardware designs and trade-off from electrical, mechanical, thermal, signal and power integrity domains.
We are hiring a senior level candidate with atleast 10+ years of experience.
Location: Sunnyvale, CA
The base salary range for this position is $210,000 to $240,000+ annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nCerebras is seeking an exceptional Senior Staff Electrical Engineer to drive our system hardware development. This role is focusing on defining and driving system architecture and strategy for high-performance compute, AI/ML accelerators and advanced ASIC platforms.\n\n\n\nResponsibilities\n\n - Lead system architecture and hardware design from concept to production release.\n\n - Own hardware development, system specification, schematic and layout design, bring up, debug, validation and system integration. \n\n - Drive future technology development with internal and industry partners. \n\n - Collaborate with various design and operations teams: manufacturing operations & test engineering, supply chain, ASIC, mechanical, signal integrity, power delivery, layout, embedded & diagnostic, etc.\n\nMinimum Qualifications\n\n - B.S.c, M.S.c, or Ph.D. degree in electrical engineering, or equivalent experience. \n\n - Minimum 10 years of experience as a board design engineer (exceptional candidates with other experience levels will also be considered). \n\n - Experience with system design, digital circuits, power delivery, voltage regulators, and high-speed signal integrity. \n\n - System-level understanding and familiarity with production environment. \n\n - Proficiency with lab/test scripting SW (e.g., Python). \n\n - Personal skills: self-instruction, multi-disciplined, multi-tasking and good interpersonal relationship.\n\n - Experience working on server hardware, AI accelerators, hardware accelerator, datacenter, AI Hardware, enterprise product, GPU, CPU, TPU, server platform etc.\n\nPreferred Qualifications\n\n - Demonstrated expertise in enterprise and data center products.\n\n - Solid background in execution from concept, bring up, development and product launch end-to-end product development cycle.\n\n - Deep technical knowledge of system hardware designs and trade-off from electrical, mechanical, thermal, signal and power integrity domains. \n\nWe are hiring a senior level candidate with atleast 10+ years of experience.\n\nLocation: Sunnyvale, CA\n\nThe base salary range for this position is $210,000 to $240,000+ annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"87943434-237a-4649-817e-2dcc20347a23","title":"Technical Lead Manager, Infrastructure Hardware (Server and Network Systems)","department":"Software Engineering ","team":"Cluster","employmentType":"FullTime","location":"United States and Canada","secondaryLocations":[],"publishedAt":"2026-08-21T16:17:32.593+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":null,"jobUrl":"https://jobs.ashbyhq.com/cerebras/87943434-237a-4649-817e-2dcc20347a23","applyUrl":"https://jobs.ashbyhq.com/cerebras/87943434-237a-4649-817e-2dcc20347a23/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
As a Technical Lead Manager, Infrastructure Hardware (Server and Network Systems) on the Cluster Architecture Team, you will provide technical leadership and drive end-to-end execution of server and network platform programs—including new product introductions (NPIs)—across Cerebras CS-3–based AI clusters. You will lead programs from requirements and technical trade-offs through vendor selection, lab bring-up, qualification, and production rollout. You will be the technical execution owner across OEM/ODM partners, component vendors, internal software/runtime teams and architects, validation/QA, and deployment/operations.
About This Role
This role combines technical leadership with hands-on execution. You must understand server, network, and system-level design deeply enough to lead technical reviews, make and document practical trade-offs, and unblock execution—while partnering closely with Compute, Server Platform, and Network Architects on broader architectural direction. You will also build shared understanding with our rack/elevations and physical datacenter design partners so that server and network changes land smoothly in real deployments, without owning physical datacenter design.
Responsibilities
Own end-to-end technical execution for server systems and network equipment in Cerebras clusters, including NPIs, platform refreshes, and major component or configuration changes.
Drive requirements gathering and technical trade-off decisions, converting inputs into executable plans with clear milestones, readiness gates, and cross-functional deliverables.
Represent Cluster Architecture in executive reviews, OKR cycles, and leadership or customer forums as needed.
Build and manage integrated execution plans across vendors and internal teams, tracking dependencies, critical paths, and risks.
Lead OEM/ODM, switch-vendor, and component-vendor engagements, including RFI/RFP activities, technical evaluations, samples, escalations, and roadmap alignment.
Partner with Compute, Server Platform, and Network Architects to translate architectural direction into platform decisions, qualification plans, acceptance criteria, and rollout strategies.
Lead NPI execution, qualification, and release readiness, including lab/staging validation, regression tracking, issue resolution, and go/no-go decisions.
Step into execution gaps as needed to drive technical issues to closure and keep server and network programs moving.
Own risk and change management into production, including versioning, rollout sequencing, and stakeholder communication.
Ensure operational readiness with deployment and fleet teams and maintain alignment with rack and physical datacenter owners on power, cooling, space, and cabling constraints.
Skills and Qualifications
B.S. or M.S. in Computer Science, Electrical/Computer Engineering, or equivalent experience.
8+ years in technical leadership, systems engineering, or technical program leadership for server, network, or infrastructure platforms from concept through production.
Experience technically leading complex server and/or datacenter network programs across OEM/ODMs, switch vendors, component suppliers, and internal engineering teams.
Strong knowledge of server architecture—including CPU/NUMA, memory bandwidth, PCIe, NIC, and storage I/O—and networking fundamentals including leaf-spine fabrics, switch platforms, optics, and high-performance interconnects.
Familiarity with Linux server fleet management, including provisioning, firmware/BIOS, drivers, and field triage.
Demonstrated ability to make sound technical decisions, guide cross-functional teams, and drive issues to closure.
Strong multi-team execution skills, including integrated planning, risk management, dependency tracking, and executive-level communication.
Ability to operate in ambiguity and keep parallel server and network workstreams aligned.
Experience with AI/ML, HPC, or performance-sensitive distributed infrastructure is a plus.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAs a Technical Lead Manager, Infrastructure Hardware (Server and Network Systems) on the Cluster Architecture Team, you will provide technical leadership and drive end-to-end execution of server and network platform programs—including new product introductions (NPIs)—across Cerebras CS-3–based AI clusters. You will lead programs from requirements and technical trade-offs through vendor selection, lab bring-up, qualification, and production rollout. You will be the technical execution owner across OEM/ODM partners, component vendors, internal software/runtime teams and architects, validation/QA, and deployment/operations.\n\nAbout This Role\n\nThis role combines technical leadership with hands-on execution. You must understand server, network, and system-level design deeply enough to lead technical reviews, make and document practical trade-offs, and unblock execution—while partnering closely with Compute, Server Platform, and Network Architects on broader architectural direction. You will also build shared understanding with our rack/elevations and physical datacenter design partners so that server and network changes land smoothly in real deployments, without owning physical datacenter design.\n\nResponsibilities\n\n - Own end-to-end technical execution for server systems and network equipment in Cerebras clusters, including NPIs, platform refreshes, and major component or configuration changes.\n\n - Drive requirements gathering and technical trade-off decisions, converting inputs into executable plans with clear milestones, readiness gates, and cross-functional deliverables.\n\n - Represent Cluster Architecture in executive reviews, OKR cycles, and leadership or customer forums as needed.\n\n - Build and manage integrated execution plans across vendors and internal teams, tracking dependencies, critical paths, and risks.\n\n - Lead OEM/ODM, switch-vendor, and component-vendor engagements, including RFI/RFP activities, technical evaluations, samples, escalations, and roadmap alignment.\n\n - Partner with Compute, Server Platform, and Network Architects to translate architectural direction into platform decisions, qualification plans, acceptance criteria, and rollout strategies.\n\n - Lead NPI execution, qualification, and release readiness, including lab/staging validation, regression tracking, issue resolution, and go/no-go decisions.\n\n - Step into execution gaps as needed to drive technical issues to closure and keep server and network programs moving.\n\n - Own risk and change management into production, including versioning, rollout sequencing, and stakeholder communication.\n\n - Ensure operational readiness with deployment and fleet teams and maintain alignment with rack and physical datacenter owners on power, cooling, space, and cabling constraints.\n\nSkills and Qualifications\n\n - B.S. or M.S. in Computer Science, Electrical/Computer Engineering, or equivalent experience.\n\n - 8+ years in technical leadership, systems engineering, or technical program leadership for server, network, or infrastructure platforms from concept through production.\n\n - Experience technically leading complex server and/or datacenter network programs across OEM/ODMs, switch vendors, component suppliers, and internal engineering teams.\n\n - Strong knowledge of server architecture—including CPU/NUMA, memory bandwidth, PCIe, NIC, and storage I/O—and networking fundamentals including leaf-spine fabrics, switch platforms, optics, and high-performance interconnects.\n\n - Familiarity with Linux server fleet management, including provisioning, firmware/BIOS, drivers, and field triage.\n\n - Demonstrated ability to make sound technical decisions, guide cross-functional teams, and drive issues to closure.\n\n - Strong multi-team execution skills, including integrated planning, risk management, dependency tracking, and executive-level communication.\n\n - Ability to operate in ambiguity and keep parallel server and network workstreams aligned.\n\n - Experience with AI/ML, HPC, or performance-sensitive distributed infrastructure is a plus.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"20dab4de-51f4-4704-8b72-5896b83ac37b","title":"Sr. Member of Technical Staff","department":"Software Engineering ","team":"Software Engineering ","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2026-05-08T19:37:52.248+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/20dab4de-51f4-4704-8b72-5896b83ac37b","applyUrl":"https://jobs.ashbyhq.com/cerebras/20dab4de-51f4-4704-8b72-5896b83ac37b/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About the Role
We are seeking a Sr. Member of Technical Staff to design and develop software features that support system resiliency and high availability across distributed environments. In this role, you will help build and maintain scalable AI inference services, develop cloud-based deployment workflows, improve system reliability through automation, and collaborate across engineering teams to deliver high-performance software solutions.
Responsibilities
Design and develop software features that support system resiliency and high availability, including automated recovery mechanisms and fault-tolerant architecture across distributed environments.
Develop and maintain cloud-based deployment workflows for AI inference software using AWS tools and services to support low-latency and scalable system performance.
Develop Python-based scripts and APIs to streamline data preprocessing, inference execution, and post-processing for real-time inference tasks.
Use parallel programming techniques (e.g., multi-threading, asynchronous processing) to maximize resource efficiency on AWS compute instances.
Develop software components to support visualization and analysis of system performance metrics, enhancing the monitoring and usability of inference services.
Develop inference software in Docker containers and define Kubernetes orchestration strategies that ensure software reliability and efficient scaling.
Develop automated scripts to detect and mitigate common failure modes, improving software system reliability.
Debug issues related to model deployment, container orchestration, and networking configurations, documenting steps to reproduce and root-cause defects.
Triage and resolve defects in the software service by analyzing logs, metrics, and distributed traces using tools like AWS CloudWatch, Grafana, or custom Python scripts.
Work with Product Management and User Experience teams to define requirements for inference service interfaces, including configuration, monitoring, and event logging.
Author detailed technical documentation for infrastructure configurations, inference workflows, and APIs, ensuring clarity for internal teams and external customers.
Document and track defects, enhancements, and release notes using tools like Jira and Git, ensuring version control and traceability.
Skills & Qualifications
Minimum Requirements
Master's degree or foreign equivalent degree in Computer Science, or a related field.
18 months of experience as an Information Security Analyst, Software Engineer, Sr. Member of Technical Staff, IT Senior Applications Engineer, or a related occupation.
Required Skills
Infrastructure-as-Code and deployment automation: Terraform, AWS CloudFormation, AWS CDK, and Ansible.
Containerization and orchestration: Docker, Kubernetes, AWS EKS, AWS Elastic Container Service (ECS), AWS Fargate, and Helm.
Compute and serverless services: AWS EC2, AWS Lambda functions, and Auto Scaling Groups.
Monitoring, logging, and distributed tracing: AWS CloudWatch, AWS X-Ray, ELK (Elasticsearch, Logstash, Kibana), Prometheus, and Grafana.
Programming languages and frameworks: Python, Node.js, JavaScript, and Flask.
Data storage and caching: PostgreSQL, Redis, and NFS.
CI/CD and version control: Jenkins and Git.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout the Role\n\nWe are seeking a Sr. Member of Technical Staff to design and develop software features that support system resiliency and high availability across distributed environments. In this role, you will help build and maintain scalable AI inference services, develop cloud-based deployment workflows, improve system reliability through automation, and collaborate across engineering teams to deliver high-performance software solutions.\n\nResponsibilities\n\n - Design and develop software features that support system resiliency and high availability, including automated recovery mechanisms and fault-tolerant architecture across distributed environments.\n\n - Develop and maintain cloud-based deployment workflows for AI inference software using AWS tools and services to support low-latency and scalable system performance.\n\n - Develop Python-based scripts and APIs to streamline data preprocessing, inference execution, and post-processing for real-time inference tasks.\n\n - Use parallel programming techniques (e.g., multi-threading, asynchronous processing) to maximize resource efficiency on AWS compute instances.\n\n - Develop software components to support visualization and analysis of system performance metrics, enhancing the monitoring and usability of inference services.\n\n - Develop inference software in Docker containers and define Kubernetes orchestration strategies that ensure software reliability and efficient scaling.\n\n - Develop automated scripts to detect and mitigate common failure modes, improving software system reliability.\n\n - Debug issues related to model deployment, container orchestration, and networking configurations, documenting steps to reproduce and root-cause defects.\n\n - Triage and resolve defects in the software service by analyzing logs, metrics, and distributed traces using tools like AWS CloudWatch, Grafana, or custom Python scripts.\n\n - Work with Product Management and User Experience teams to define requirements for inference service interfaces, including configuration, monitoring, and event logging.\n\n - Author detailed technical documentation for infrastructure configurations, inference workflows, and APIs, ensuring clarity for internal teams and external customers.\n\n - Document and track defects, enhancements, and release notes using tools like Jira and Git, ensuring version control and traceability.\n\nSkills & Qualifications\n\nMinimum Requirements\n\n - Master's degree or foreign equivalent degree in Computer Science, or a related field.\n\n - 18 months of experience as an Information Security Analyst, Software Engineer, Sr. Member of Technical Staff, IT Senior Applications Engineer, or a related occupation.\n\n - Required Skills\n\n - Infrastructure-as-Code and deployment automation: Terraform, AWS CloudFormation, AWS CDK, and Ansible.\n\n - Containerization and orchestration: Docker, Kubernetes, AWS EKS, AWS Elastic Container Service (ECS), AWS Fargate, and Helm.\n\n - Compute and serverless services: AWS EC2, AWS Lambda functions, and Auto Scaling Groups.\n\n - Monitoring, logging, and distributed tracing: AWS CloudWatch, AWS X-Ray, ELK (Elasticsearch, Logstash, Kibana), Prometheus, and Grafana.\n\n - Programming languages and frameworks: Python, Node.js, JavaScript, and Flask.\n\n - Data storage and caching: PostgreSQL, Redis, and NFS.\n\n - CI/CD and version control: Jenkins and Git.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"bf35e329-997b-438b-8dab-da21a59a6222","title":"Sr. Technical Staff","department":"Software Engineering ","team":"Software Engineering ","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2026-05-08T19:40:37.861+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/bf35e329-997b-438b-8dab-da21a59a6222","applyUrl":"https://jobs.ashbyhq.com/cerebras/bf35e329-997b-438b-8dab-da21a59a6222/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About the Role
We are seeking a Sr. Technical Staff to support the post-silicon validation of Cerebras Wafer Scale Engines. In this role, you will test and debug new silicon, develop automation and debug tools, support wafer bring-up and manufacturing operations, and collaborate across hardware and software engineering teams to ensure high-quality system performance.
Responsibilities
Perform post-silicon validation of Cerebras Wafer Scale Engines. Test and debug issues on new silicon.
Test, analyze, and characterize high-speed serial interfaces to verify compliance with hardware specifications, record performance data, and recommend design modifications to optimize functionality.
Work with the silicon and operations team to test, bring up, and run burn-in on wafer-scale systems.
Support manufacturing operations to utilize the wafer bring-up flow. Perform wafer bring-ups, diagnose, and debug problems encountered.
Develop and implement hardware to ensure compliance with design specifications.
Collaborate with hardware design engineers and system software engineers to review specifications and recommend changes that will improve the quality and verifiability of the hardware designs.
Create and maintain automated regression test scripts, using Python and/or Bash, that ensure all tests are run and pass after each change to the design, testbench, tests, or reference model.
Work with system team members to diagnose system-related failures. Understand the key system interfaces to FPGAs, power, and cooling, and apply that knowledge to the debug of silicon features.
Develop debug tools in Python to program and analyze the behavior of the Wafer Scale Engine.
Develop wafer bring-up flow utilizing Python and shell scripts to capture the steps required to bring up a wafer in a logical, easy-to-use flow.
Document issues found, tools, and flow.
Skills & Qualifications
Minimum Requirements
Master's degree or foreign equivalent degree in Electrical Engineering, Computer Engineering, or a related field.
Three (3) years of experience as an Application Engineer, Sr. Technical Staff, Hardware Engineer, or a related occupation.
Required Skills
Electrical Signal Integrity Analysis.
Hardware Bring-up & Debug.
Functional and Electrical Characterization.
Test automation using scripting language.
High-Speed Interfaces & Protocols, including Ethernet, CPRI, or Interlaken.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout the Role\n\nWe are seeking a Sr. Technical Staff to support the post-silicon validation of Cerebras Wafer Scale Engines. In this role, you will test and debug new silicon, develop automation and debug tools, support wafer bring-up and manufacturing operations, and collaborate across hardware and software engineering teams to ensure high-quality system performance.\n\nResponsibilities\n\n - Perform post-silicon validation of Cerebras Wafer Scale Engines. Test and debug issues on new silicon.\n\n - Test, analyze, and characterize high-speed serial interfaces to verify compliance with hardware specifications, record performance data, and recommend design modifications to optimize functionality.\n\n - Work with the silicon and operations team to test, bring up, and run burn-in on wafer-scale systems.\n\n - Support manufacturing operations to utilize the wafer bring-up flow. Perform wafer bring-ups, diagnose, and debug problems encountered.\n\n - Develop and implement hardware to ensure compliance with design specifications.\n\n - Collaborate with hardware design engineers and system software engineers to review specifications and recommend changes that will improve the quality and verifiability of the hardware designs.\n\n - Create and maintain automated regression test scripts, using Python and/or Bash, that ensure all tests are run and pass after each change to the design, testbench, tests, or reference model.\n\n - Work with system team members to diagnose system-related failures. Understand the key system interfaces to FPGAs, power, and cooling, and apply that knowledge to the debug of silicon features.\n\n - Develop debug tools in Python to program and analyze the behavior of the Wafer Scale Engine.\n\n - Develop wafer bring-up flow utilizing Python and shell scripts to capture the steps required to bring up a wafer in a logical, easy-to-use flow.\n\n - Document issues found, tools, and flow.\n\nSkills & Qualifications\n\nMinimum Requirements\n\n - Master's degree or foreign equivalent degree in Electrical Engineering, Computer Engineering, or a related field.\n\n - Three (3) years of experience as an Application Engineer, Sr. Technical Staff, Hardware Engineer, or a related occupation.\n\n - Required Skills\n\n - Electrical Signal Integrity Analysis.\n\n - Hardware Bring-up & Debug.\n\n - Functional and Electrical Characterization.\n\n - Test automation using scripting language.\n\n - High-Speed Interfaces & Protocols, including Ethernet, CPRI, or Interlaken.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"24e42002-7f6d-4769-9ce0-0d844757cc0e","title":"Member of Technical Staff (Software Engineer) ","department":"Software Engineering ","team":"Inference Service","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2026-05-08T19:43:17.308+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/24e42002-7f6d-4769-9ce0-0d844757cc0e","applyUrl":"https://jobs.ashbyhq.com/cerebras/24e42002-7f6d-4769-9ce0-0d844757cc0e/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
We are seeking a Software Engineer to develop and maintain high-performance, low-latency inference infrastructure. This role focuses on deploying and optimizing scalable inference services, collaborating with cross-functional teams, and ensuring reliable, production-ready machine learning infrastructure.
Responsibilities
Implement infrastructure to support high-performance, low-latency inference service.
Deploy and configure Kubernetes services to ensure scalability and reliability of inference workloads.
Optimize resource allocation and auto-scaling policies to handle variable inference demand while minimizing operational costs.
Integrate inference services with containerized environments using Docker and Kubernetes for orchestration.
Ensure high availability and fault tolerance by implementing multi-region deployments and disaster recovery strategies.
Develop Python-based scripts and APIs to streamline data preprocessing, inference execution, and post-processing for real-time inference tasks.
Collaborate with machine learning engineers to validate inference accuracy and performance against functional and latency requirements.
Triage and resolve defects in the service by analyzing logs, metrics, and distributed traces.
Debug issues related to model deployment, container orchestration, or networking configurations, documenting steps to reproduce and root-cause defects.
Collaborate with cross-functional teams to address performance regressions, scalability issues, or integration failures in the inference pipeline.
Develop automated scripts to detect and mitigate common failure modes, improving system reliability.
Author detailed technical documentation for infrastructure configurations, inference workflows, and APIs, ensuring clarity for internal teams and external customers.
Work with product management and user experience teams to define requirements for inference service interfaces, including configuration, monitoring, and event logging.
Document and track defects, enhancements, and release notes using tools like Jira and Git, ensuring version control and traceability.
Participate in release planning and prioritization discussions to align infrastructure development with customer needs and business objectives.
Skills & Qualifications
Master's degree (or foreign equivalent) in Computer Science or a related field.
One (1) year of experience as a Software Developer, Student/Intern (Software Developer), Member of Technical Staff (Software Engineer), Software Engineer, or a related occupation.
Employer accepts full-time or equivalent part-time experience gained before, during, or after graduate studies.
Required Skills:
Docker and Kubernetes;
Java or C++;
ActiveMQ and Kafka;
Python or Groovy;
JavaScript or TypeScript;
Linux;
SQL, OracleDB, and Redis; and
Git
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\nWe are seeking a Software Engineer to develop and maintain high-performance, low-latency inference infrastructure. This role focuses on deploying and optimizing scalable inference services, collaborating with cross-functional teams, and ensuring reliable, production-ready machine learning infrastructure.\nResponsibilities\n\n - Implement infrastructure to support high-performance, low-latency inference service.\n\n - Deploy and configure Kubernetes services to ensure scalability and reliability of inference workloads.\n\n - Optimize resource allocation and auto-scaling policies to handle variable inference demand while minimizing operational costs.\n\n - Integrate inference services with containerized environments using Docker and Kubernetes for orchestration.\n\n - Ensure high availability and fault tolerance by implementing multi-region deployments and disaster recovery strategies.\n\n - Develop Python-based scripts and APIs to streamline data preprocessing, inference execution, and post-processing for real-time inference tasks.\n\n - Collaborate with machine learning engineers to validate inference accuracy and performance against functional and latency requirements.\n\n - Triage and resolve defects in the service by analyzing logs, metrics, and distributed traces.\n\n - Debug issues related to model deployment, container orchestration, or networking configurations, documenting steps to reproduce and root-cause defects.\n\n - Collaborate with cross-functional teams to address performance regressions, scalability issues, or integration failures in the inference pipeline.\n\n - Develop automated scripts to detect and mitigate common failure modes, improving system reliability.\n\n - Author detailed technical documentation for infrastructure configurations, inference workflows, and APIs, ensuring clarity for internal teams and external customers.\n\n - Work with product management and user experience teams to define requirements for inference service interfaces, including configuration, monitoring, and event logging.\n\n - Document and track defects, enhancements, and release notes using tools like Jira and Git, ensuring version control and traceability.\n\n - Participate in release planning and prioritization discussions to align infrastructure development with customer needs and business objectives.\n\nSkills & Qualifications\n\n\nMINIMUM REQUIREMENTS\n\n - Master's degree (or foreign equivalent) in Computer Science or a related field.\n\n - One (1) year of experience as a Software Developer, Student/Intern (Software Developer), Member of Technical Staff (Software Engineer), Software Engineer, or a related occupation.\n\n - Employer accepts full-time or equivalent part-time experience gained before, during, or after graduate studies.\n\nRequired Skills:\n\n - Docker and Kubernetes;\n\n - Java or C++;\n\n - ActiveMQ and Kafka;\n\n - Python or Groovy;\n\n - JavaScript or TypeScript;\n\n - Linux;\n\n - SQL, OracleDB, and Redis; and\n\n - Git\n\n\n\n \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"99c289fa-8fc6-49f7-b7e8-78ac4e9d99ac","title":"Software Engineer - New Grad 2026","department":"University Departments","team":"New Grads","employmentType":"FullTime","location":"Toronto, CAN","secondaryLocations":[],"publishedAt":"2026-05-11T19:38:35.637+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressRegion":"Ontario ","addressCountry":"Canada","addressLocality":"Toronto "}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/99c289fa-8fc6-49f7-b7e8-78ac4e9d99ac","applyUrl":"https://jobs.ashbyhq.com/cerebras/99c289fa-8fc6-49f7-b7e8-78ac4e9d99ac/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
As a New Graduate Software Engineer, you will collaborate with world-class engineers to solve real-world challenges across the software stack. You will contribute to software systems that directly impact performance, scalability, reliability, and usability of next-generation AI infrastructure.
This role is ideal for candidates with a strong interest in systems programming, networking, embedded systems, distributed infrastructure, or performance-oriented software engineering. Our teams work very closely with hardware, so candidates with experience primarily focused on higher-level application development or AI applications may be less aligned with the nature of this work.
You will gain hands-on experience working across multiple layers of a fully integrated AI-accelerated system, including advanced hardware interfaces, low-level infrastructure, distributed systems, compilers, and ML frameworks.
Collaborate with experienced engineers on real-world systems and infrastructure challenges.
Design, implement, test, and debug software solutions that directly impact system performance and reliability.
Contribute to low-level software components interacting closely with hardware and networking infrastructure.
Learn and contribute across multiple layers of a fully integrated AI-accelerated platform.
Participate in debugging, performance optimization, and system bring-up activities.
Develop tools and infrastructure to improve observability, reliability, and scalability.
Work cross-functionally with hardware, firmware, compiler, and infrastructure teams.
Recently graduated or currently enrolled in a university program in Computer Science, Computer Engineering, Electrical Engineering, or a related discipline (graduating in 2026).
Proficiency in C/C++ programming languages
Interest or exposure to systems/socket programming, networking, embedded systems, operating systems, device drivers, distributed systems, or network performance.
Desire to work close to hardware/network and learn low-level engineering concepts.
Detail-oriented but keen to learn the bigger picture and step out of comfort zone.
Excellent communication and collaboration skills.
Hybrid role based in Toronto, ON, or Sunnyvale CA
Experience with Linux systems programming or debugging tools.
Familiarity with TCP/RDMA protocols, RPCs, and packet trace tools such as Wireshark
Exposure to networking concepts, device drivers, embedded systems, or distributed infrastructure.
Familiarity with performance optimization or concurrent programming concepts.
Interest in large-scale AI infrastructure and accelerated computing systems.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n\nABOUT THE ROLE\n\nAs a New Graduate Software Engineer, you will collaborate with world-class engineers to solve real-world challenges across the software stack. You will contribute to software systems that directly impact performance, scalability, reliability, and usability of next-generation AI infrastructure.\n\nThis role is ideal for candidates with a strong interest in systems programming, networking, embedded systems, distributed infrastructure, or performance-oriented software engineering. Our teams work very closely with hardware, so candidates with experience primarily focused on higher-level application development or AI applications may be less aligned with the nature of this work.\n\nYou will gain hands-on experience working across multiple layers of a fully integrated AI-accelerated system, including advanced hardware interfaces, low-level infrastructure, distributed systems, compilers, and ML frameworks.\n\n\nRESPONSIBILITIES\n\n - Collaborate with experienced engineers on real-world systems and infrastructure challenges.\n\n - Design, implement, test, and debug software solutions that directly impact system performance and reliability.\n\n - Contribute to low-level software components interacting closely with hardware and networking infrastructure.\n\n - Learn and contribute across multiple layers of a fully integrated AI-accelerated platform.\n\n - Participate in debugging, performance optimization, and system bring-up activities.\n\n - Develop tools and infrastructure to improve observability, reliability, and scalability.\n\n - Work cross-functionally with hardware, firmware, compiler, and infrastructure teams.\n\n\nREQUIRED QUALIFICATIONS\n\n - Recently graduated or currently enrolled in a university program in Computer Science, Computer Engineering, Electrical Engineering, or a related discipline (graduating in 2026).\n\n - Proficiency in C/C++ programming languages\n\n - Interest or exposure to systems/socket programming, networking, embedded systems, operating systems, device drivers, distributed systems, or network performance.\n\n - Desire to work close to hardware/network and learn low-level engineering concepts.\n\n - Detail-oriented but keen to learn the bigger picture and step out of comfort zone.\n\n - Excellent communication and collaboration skills.\n\n - Hybrid role based in Toronto, ON, or Sunnyvale CA\n\n\nASSETS\n\n - Experience with Linux systems programming or debugging tools.\n\n - Familiarity with TCP/RDMA protocols, RPCs, and packet trace tools such as Wireshark\n\n - Exposure to networking concepts, device drivers, embedded systems, or distributed infrastructure.\n\n - Familiarity with performance optimization or concurrent programming concepts.\n\n - Interest in large-scale AI infrastructure and accelerated computing systems.\n\n \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"40e0d3ee-8f0a-4b19-9bf9-79410b1c7735","title":"DevOps Engineer - New Grad 2026","department":"University Departments","team":"New Grads","employmentType":"FullTime","location":"Toronto, CAN","secondaryLocations":[],"publishedAt":"2026-05-11T20:00:47.834+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressRegion":"Ontario ","addressCountry":"Canada","addressLocality":"Toronto "}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/40e0d3ee-8f0a-4b19-9bf9-79410b1c7735","applyUrl":"https://jobs.ashbyhq.com/cerebras/40e0d3ee-8f0a-4b19-9bf9-79410b1c7735/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
As a New Graduate Software Engineer, you will collaborate with world-class engineers to solve real-world challenges across the software stack. You will contribute to software systems that directly impact performance, scalability, reliability, and usability of next-generation AI infrastructure.
You will gain hands-on experience working across multiple layers of a fully integrated AI-accelerated system, including advanced hardware interfaces, low-level infrastructure, distributed systems, compilers, and ML frameworks.
You will develop and maintain the infrastructure required to build, test, operate, simulate, and evaluate the Cerebras software stack. As a DevOps engineer, you will be responsible for designing efficient, scalable workflows for automating processes in the cloud and in our datacenter. You will work closely with the development and product management teams to monitor the quality and performance of the software that runs on the Wafer Scale Engine (WSE), the world’s largest and fastest AI computer.
Required Qualifications
Enrolled in a University program with a degree in Computer Science, Computer Engineering, or other related disciplines.
Experience in software development environments.
Proficient in Python, shell scripting, Makefiles.
Strong end-to-end triage, debug, and troubleshooting skills.
Experience with Jenkins and other CI/CD platforms.
Experience with Docker, Kubernetes and container technology in general.
Experience building services on top of AWS or other cloud platforms at scale.
UI experience highly desirable.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n\nABOUT THE ROLE\n\nAs a New Graduate Software Engineer, you will collaborate with world-class engineers to solve real-world challenges across the software stack. You will contribute to software systems that directly impact performance, scalability, reliability, and usability of next-generation AI infrastructure.\n\nYou will gain hands-on experience working across multiple layers of a fully integrated AI-accelerated system, including advanced hardware interfaces, low-level infrastructure, distributed systems, compilers, and ML frameworks.\n\n\nRESPONSIBILITIES\n\nYou will develop and maintain the infrastructure required to build, test, operate, simulate, and evaluate the Cerebras software stack. As a DevOps engineer, you will be responsible for designing efficient, scalable workflows for automating processes in the cloud and in our datacenter. You will work closely with the development and product management teams to monitor the quality and performance of the software that runs on the Wafer Scale Engine (WSE), the world’s largest and fastest AI computer. \n\nRequired Qualifications \n\n - Enrolled in a University program with a degree in Computer Science, Computer Engineering, or other related disciplines. \n\n - Experience in software development environments. \n\n - Proficient in Python, shell scripting, Makefiles. \n\n - Strong end-to-end triage, debug, and troubleshooting skills. \n\n - Experience with Jenkins and other CI/CD platforms. \n\n - Experience with Docker, Kubernetes and container technology in general. \n\n - Experience building services on top of AWS or other cloud platforms at scale. \n\n - UI experience highly desirable. \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"864698cd-da36-42b6-bbcc-fc39d22010f0","title":"AI Engineer, Model Quality and Performance","department":"Software Engineering ","team":"Software Engineering ","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2026-05-15T12:28:49.572+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/864698cd-da36-42b6-bbcc-fc39d22010f0","applyUrl":"https://jobs.ashbyhq.com/cerebras/864698cd-da36-42b6-bbcc-fc39d22010f0/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
You'll own model quality and performance for Cerebras' inference offerings. You will define what \"good\" looks like across the models we serve, building AI-driven systems to measure it at scale, and translating those signals into artifacts our customers and product team actually use.
You'll use AI agents to spin up custom eval suites per customer use case, mine trajectories for representative test data, automate the repetitive parts of release qual, and help build performance datasets and benchmarking workflows for customer use cases. We want someone whose first instinct is \"how do I get an AI agent to do this on a loop.\"
You'll sit between engineering, product, and customer-facing teams.
What You'll Do
Design eval suites with AI agents in the loop. For every model release, curate a thoughtful mix of advanced, basic, long-context, and customer-use-case-specific evals. Use Claude to generate, validate, and prune candidate test cases at speed.
Build custom evals for target customers by orchestrating AI agents to mine trajectories from their workloads and synthesize representative eval sets.
Automate eval execution end-to-end with AI-driven pipelines on top of standard tooling (Docker, Git, CI). The goal is a system that runs itself between releases, not a script you re-run by hand.
Build automations to forecast and benchmark model performance on Cerebras for our top customers, including modeling how fast customer-specific workloads will run in production.
Build product-quality tooling that synthesizes quality + performance data into a single, easy-to-use view.
Experience building AI agents. You ship real systems with Claude (or equivalent) as a force multiplier. You've built things that would have been infeasible solo without AI agents in the loop.
Strong math/stats background..
Comfort with Docker, Git, and the standard automation stack
A taste for tooling design. You've shipped something that a non-engineer used without complaining. Bonus if AI helped you ship it.
Performance-tuning experience on custom silicon, GPUs, or FPGAs.
Experience designing evals for agentic / coding / long-context / multimodal use cases.
Familiarity with open-source eval frameworks (EvalScope, lm-eval-harness, etc.).
Experience building AI agents.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n\nABOUT THE ROLE\n\nYou'll own model quality and performance for Cerebras' inference offerings. You will define what \"good\" looks like across the models we serve, building AI-driven systems to measure it at scale, and translating those signals into artifacts our customers and product team actually use.\n\nYou'll use AI agents to spin up custom eval suites per customer use case, mine trajectories for representative test data, automate the repetitive parts of release qual, and help build performance datasets and benchmarking workflows for customer use cases. We want someone whose first instinct is \"how do I get an AI agent to do this on a loop.\"\n\nYou'll sit between engineering, product, and customer-facing teams. \n\nWhat You'll Do\n\n - Design eval suites with AI agents in the loop. For every model release, curate a thoughtful mix of advanced, basic, long-context, and customer-use-case-specific evals. Use Claude to generate, validate, and prune candidate test cases at speed.\n\n - Build custom evals for target customers by orchestrating AI agents to mine trajectories from their workloads and synthesize representative eval sets.\n\n - Automate eval execution end-to-end with AI-driven pipelines on top of standard tooling (Docker, Git, CI). The goal is a system that runs itself between releases, not a script you re-run by hand.\n\n - Build automations to forecast and benchmark model performance on Cerebras for our top customers, including modeling how fast customer-specific workloads will run in production.\n\n - Build product-quality tooling that synthesizes quality + performance data into a single, easy-to-use view. \n\n\nSKILLS & QUALIFICATIONS\n\n - Experience building AI agents. You ship real systems with Claude (or equivalent) as a force multiplier. You've built things that would have been infeasible solo without AI agents in the loop.\n\n - Strong math/stats background..\n\n - Comfort with Docker, Git, and the standard automation stack\n\n - A taste for tooling design. You've shipped something that a non-engineer used without complaining. Bonus if AI helped you ship it.\n\n\nASSETS\n\n - Performance-tuning experience on custom silicon, GPUs, or FPGAs. \n\n - Experience designing evals for agentic / coding / long-context / multimodal use cases.\n\n - Familiarity with open-source eval frameworks (EvalScope, lm-eval-harness, etc.).\n\n - Experience building AI agents.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"fd32728a-5801-42fd-aeb5-c5e4dfbd9403","title":"Senior Staff Design Verification Engineer","department":"Hardware","team":"Silicon","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2026-08-07T22:52:52.769+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/fd32728a-5801-42fd-aeb5-c5e4dfbd9403","applyUrl":"https://jobs.ashbyhq.com/cerebras/fd32728a-5801-42fd-aeb5-c5e4dfbd9403/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Key Responsibilities
Work with architects, designers, post silicon and software engineers to ensure a high-quality design that works first silicon.
Develop and implement verification strategies, detailed tests and coverage plans based on micro-architecture.
Create verification methodologies and reusable environments, including components such as stimulus, checkers, assertions, and coverage.
Implement tests, manage regressions, gather coverage, and debug test failures.
Collaborate with cross-functional teams including architecture, RTL design, physical design, firmware, and validation.
Analyze and debug complex issues across simulation, emulation, and silicon bring-up phases.
Continuously enhances verification infrastructure and flows to improve efficiency and quality.
Contribute to the evolution of the overall verification methodology and best practices across the organization.
Skills and Qualifications
Great debugging and problem-solving skills.
Deep knowledge of SystemVerilog testbench, DPI and UVM.
Excellent programming skills and knowledge of software engineering practices including object-oriented design.
Experience developing scalable and portable testbenches and components.
Experience with verification methodologies and tools such as simulators, waveform viewers, build and run automation, coverage collection, and gate level simulations.
Proficient in scripting languages such as Python or Perl.
Good interpersonal skills and the ability to work as a standout colleague are a must.
Extremely self-motivated and eager to solve problems
15+ years of Design Verification experience.
Desired Skills and Qualifications
Knowledge of pipelined processor architecture.
BS or MS in Computer Science or Electrical Engineering.
15+ years of hands-on Design Verification experience.
Location: Sunnyvale, CA
The base salary range for this position is $250,000 to $300,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nKey Responsibilities\n\n - Work with architects, designers, post silicon and software engineers to ensure a high-quality design that works first silicon.\n\n - Develop and implement verification strategies, detailed tests and coverage plans based on micro-architecture.\n\n - Create verification methodologies and reusable environments, including components such as stimulus, checkers, assertions, and coverage.\n\n - Implement tests, manage regressions, gather coverage, and debug test failures.\n\n - Collaborate with cross-functional teams including architecture, RTL design, physical design, firmware, and validation.\n\n - Analyze and debug complex issues across simulation, emulation, and silicon bring-up phases.\n\n - Continuously enhances verification infrastructure and flows to improve efficiency and quality.\n\n - Contribute to the evolution of the overall verification methodology and best practices across the organization.\n\nSkills and Qualifications\n\n - Great debugging and problem-solving skills.\n\n - Deep knowledge of SystemVerilog testbench, DPI and UVM.\n\n - Excellent programming skills and knowledge of software engineering practices including object-oriented design.\n\n - Experience developing scalable and portable testbenches and components.\n\n - Experience with verification methodologies and tools such as simulators, waveform viewers, build and run automation, coverage collection, and gate level simulations.\n\n - Proficient in scripting languages such as Python or Perl.\n\n - Good interpersonal skills and the ability to work as a standout colleague are a must.\n\n - Extremely self-motivated and eager to solve problems\n\n - 15+ years of Design Verification experience.\n\nDesired Skills and Qualifications\n\n - Knowledge of pipelined processor architecture.\n\n - BS or MS in Computer Science or Electrical Engineering.\n\n - 15+ years of hands-on Design Verification experience.\n\nLocation: Sunnyvale, CA\n\nThe base salary range for this position is $250,000 to $300,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.\n\n \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"45dec7be-c0c1-40fe-a88d-d13db4f44e42","title":"Design Verification Engineer","department":"Hardware","team":"Silicon","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2026-06-04T18:24:18.201+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/45dec7be-c0c1-40fe-a88d-d13db4f44e42","applyUrl":"https://jobs.ashbyhq.com/cerebras/45dec7be-c0c1-40fe-a88d-d13db4f44e42/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Key Responsibilities
Work with architects, designers, post silicon and software engineers to ensure a high-quality design that works for silicon.
Develop and implement verification strategies, detailed tests and coverage plans based on micro-architecture.
Create verification methodologies and reusable environments, including components such as stimulus, checkers, assertions, and coverage.
Implement tests, manage regressions, gather coverage, and debug test failures.
Collaborate with cross-functional teams including architecture, RTL design, physical design, firmware, and validation.
Analyze and debug complex issues across simulation, emulation, and silicon bring-up phases.
Continuously enhances verification infrastructure and flows to improve efficiency and quality.
Contribute to the evolution of the overall verification methodology and best practices across the organization.
Skills and Qualifications
Great debugging and problem-solving skills.
Deep knowledge of SystemVerilog testbench, DPI and UVM.
Excellent programming skills and knowledge of software engineering practices including object-oriented design.
Experience developing scalable and portable testbenches and components.
Experience with verification methodologies and tools such as simulators, waveform viewers, build and run automation, coverage collection, and gate level simulations.
Proficient in scripting languages such as Python or Perl.
Good interpersonal skills and the ability to work as a standout colleague are a must.
Extremely self-motivated and eager to solve problems
3-5+ years of Design Verification experience.
Desired Skills and Qualifications
Knowledge of pipelined processor architecture.
BS or MS in Computer Science or Electrical Engineering.
3-5+ years of hands-on Design Verification experience.
Location: Sunnyvale, CA
The base salary range for this position is $190,000 to $230,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nKey Responsibilities\n\n - Work with architects, designers, post silicon and software engineers to ensure a high-quality design that works for silicon.\n\n - Develop and implement verification strategies, detailed tests and coverage plans based on micro-architecture.\n\n - Create verification methodologies and reusable environments, including components such as stimulus, checkers, assertions, and coverage.\n\n - Implement tests, manage regressions, gather coverage, and debug test failures.\n\n - Collaborate with cross-functional teams including architecture, RTL design, physical design, firmware, and validation.\n\n - Analyze and debug complex issues across simulation, emulation, and silicon bring-up phases.\n\n - Continuously enhances verification infrastructure and flows to improve efficiency and quality.\n\n - Contribute to the evolution of the overall verification methodology and best practices across the organization.\n\nSkills and Qualifications\n\n - Great debugging and problem-solving skills.\n\n - Deep knowledge of SystemVerilog testbench, DPI and UVM.\n\n - Excellent programming skills and knowledge of software engineering practices including object-oriented design.\n\n - Experience developing scalable and portable testbenches and components.\n\n - Experience with verification methodologies and tools such as simulators, waveform viewers, build and run automation, coverage collection, and gate level simulations.\n\n - Proficient in scripting languages such as Python or Perl.\n\n - Good interpersonal skills and the ability to work as a standout colleague are a must.\n\n - Extremely self-motivated and eager to solve problems\n\n - 3-5+ years of Design Verification experience.\n\nDesired Skills and Qualifications\n\n - Knowledge of pipelined processor architecture.\n\n - BS or MS in Computer Science or Electrical Engineering.\n\n - 3-5+ years of hands-on Design Verification experience.\n\nLocation: Sunnyvale, CA\n\nThe base salary range for this position is $190,000 to $230,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.\n\n \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"d0baac54-76cb-4e8d-93bd-24e121113870","title":"Physical Design Engineer","department":"Hardware","team":"Silicon","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2026-06-10T15:46:29.974+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/d0baac54-76cb-4e8d-93bd-24e121113870","applyUrl":"https://jobs.ashbyhq.com/cerebras/d0baac54-76cb-4e8d-93bd-24e121113870/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
Join our close-knit physical design team where you'll excel in synthesizing, placing, and routing high speed designs. Experience the full spectrum of physical design and implementation, collaborating closely with the RTL team and integrating these blocks seamlessly into the full-chip architecture.
Skills and Qualifications
Required:
10+ years of physical design/verification experience.
Strong knowledge of block level and full-chip physical verification methodology.
Strong background in block physical design, Synthesis, PDV and IR.
Expert at optimizing for the best power/performance and area.
Experience with the complete physical design flow. Knowledge of Synopsys tool suite is a plus.
Expert with ICV or Calibre tools resolving block and full-chip DRC and LVS issues.
Expert with IR/EM analysis and resolution.
Strong ability in scripting languages like Tcl and Python. Ability to make flow enhancements.
Demonstrated ability to work with RTL teams to optimize for physical design.
Should demonstrate ownership, deep dive and should demonstrate strong fundamental understanding of PD concepts.
Preferred:
Experience doing full chip floor planning and integration.
Knowledge of clock distribution.
Knowledge of cooling analysis.
STA would be good to have.
Knowledge of 2.5D or 3D packaging solutions.
The salary range for this position is $230,000 – $280,000 annually. Actual compensation will be determined based on factors such as experience, skills, qualifications, and location.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nJoin our close-knit physical design team where you'll excel in synthesizing, placing, and routing high speed designs. Experience the full spectrum of physical design and implementation, collaborating closely with the RTL team and integrating these blocks seamlessly into the full-chip architecture.\n\nSkills and Qualifications\n\nRequired:\n\n - 10+ years of physical design/verification experience.\n\n - Strong knowledge of block level and full-chip physical verification methodology.\n\n - Strong background in block physical design, Synthesis, PDV and IR.\n\n - Expert at optimizing for the best power/performance and area.\n\n - Experience with the complete physical design flow. Knowledge of Synopsys tool suite is a plus.\n\n - Expert with ICV or Calibre tools resolving block and full-chip DRC and LVS issues.\n\n - Expert with IR/EM analysis and resolution.\n\n - Strong ability in scripting languages like Tcl and Python. Ability to make flow enhancements.\n\n - Demonstrated ability to work with RTL teams to optimize for physical design.\n\n - Should demonstrate ownership, deep dive and should demonstrate strong fundamental understanding of PD concepts.\n \n \n\n\n\nPreferred:\n\n - Experience doing full chip floor planning and integration.\n\n - Knowledge of clock distribution.\n\n - Knowledge of cooling analysis.\n\n - STA would be good to have.\n\n - Knowledge of 2.5D or 3D packaging solutions.\n\n\n\nThe salary range for this position is $230,000 – $280,000 annually. Actual compensation will be determined based on factors such as experience, skills, qualifications, and location.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"474768a4-7e4f-43c9-a9d3-f23dfe6be406","title":"ML Systems Performance Engineer","department":"Software Engineering ","team":"Inference Core","employmentType":"FullTime","location":"Bengaluru, IND","secondaryLocations":[],"publishedAt":"2026-06-16T06:41:30.545+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"Karnataka","addressCountry":"India","addressLocality":"Bengaluru"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/474768a4-7e4f-43c9-a9d3-f23dfe6be406","applyUrl":"https://jobs.ashbyhq.com/cerebras/474768a4-7e4f-43c9-a9d3-f23dfe6be406/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Engineers on the inference performance team operate at the intersection of hardware and software, driving end-to-end model inference speed and throughput. Their work spans low-level kernel performance debugging and optimization, system-level performance analysis, performance modeling and estimation, and the development of tooling for performance projection and diagnostics.
Build performance models (kernel-level, end-to-end) to estimate the performance of state of the art and customer ML models.
Optimize and debug our kernel micro code and compiler algorithms to elevate ML model inference speed, throughput and compute utilization on the Cerebras WSE.
Debug and understand runtime performance on the system and cluster.
Develop tools and infrastructure to help visualize performance data collected from the Wafer Scale Engine and our compute cluster.
Bachelors / Masters / PhD in Electrical Engineering or Computer Science.
Strong background in computer architecture.
Exposure to and understanding of low-level deep learning / LLM math.
Strong analytical and problem-solving mindset.
3+ years of experience in a relevant domain (Computer Architecture, CPU/GPU Performance, Kernel Optimization, HPC).
Experience working on CPU/GPU simulators.
Exposure to performance profiling and debug on any system pipeline.
Comfort with C++ and Python.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n\nABOUT THE ROLE\n\nEngineers on the inference performance team operate at the intersection of hardware and software, driving end-to-end model inference speed and throughput. Their work spans low-level kernel performance debugging and optimization, system-level performance analysis, performance modeling and estimation, and the development of tooling for performance projection and diagnostics.\n\n\nRESPONSIBILITIES\n\n - Build performance models (kernel-level, end-to-end) to estimate the performance of state of the art and customer ML models.\n\n - Optimize and debug our kernel micro code and compiler algorithms to elevate ML model inference speed, throughput and compute utilization on the Cerebras WSE.\n\n - Debug and understand runtime performance on the system and cluster.\n\n - Develop tools and infrastructure to help visualize performance data collected from the Wafer Scale Engine and our compute cluster.\n\n\nREQUIREMENTS\n\n - Bachelors / Masters / PhD in Electrical Engineering or Computer Science.\n\n - Strong background in computer architecture.\n\n - Exposure to and understanding of low-level deep learning / LLM math.\n\n - Strong analytical and problem-solving mindset.\n\n - 3+ years of experience in a relevant domain (Computer Architecture, CPU/GPU Performance, Kernel Optimization, HPC).\n\n - Experience working on CPU/GPU simulators.\n\n - Exposure to performance profiling and debug on any system pipeline.\n\n - Comfort with C++ and Python.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"224566db-c2c9-4b81-9534-a9917ea1aaa6","title":"Cloud Quality Engineer","department":"Software Engineering ","team":"Inference Service","employmentType":"FullTime","location":"Bengaluru, IND","secondaryLocations":[],"publishedAt":"2026-07-02T15:50:58.787+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressRegion":"Karnataka ","addressCountry":"India","addressLocality":"Bengaluru"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/224566db-c2c9-4b81-9534-a9917ea1aaa6","applyUrl":"https://jobs.ashbyhq.com/cerebras/224566db-c2c9-4b81-9534-a9917ea1aaa6/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
The Cloud Quality team is responsible for the confidence behind every production release shipped to Cerebras Inference Cloud.
We work closely with platform, infrastructure, ML systems, and product engineering teams to ensure that rapid iteration never comes at the expense of customer trust. Our environment spans distributed cloud systems, multi-region deployments, APIs, orchestration layers, and hardware-backed inference services.
We are scaling quickly. The systems are growing in complexity, traffic is increasing rapidly, and release velocity remains high. We need engineers who can build quality systems that scale with the business.
About the role
We are hiring a Cloud Quality Engineer to own the quality of our weekly cloud releases end to end and to build the test infrastructure that lets the team scale. This is a hands-on senior IC role for someone who treats quality as a first-class engineering problem - not a downstream gate.
You will drive every release from branch cut to sign-off, build scalable test infrastructure that grows with customer load, and push back when quality is at risk. You will operate effectively across timezones, async-first, with clear written communication.
This is a role for someone who self-drives. You will frequently work without complete product specifications, decide under ambiguity, and ask the right questions before code lands - not after.
Responsibilities
- Release Quality Ownership: Drive weekly cloud release qualification end to end. Read every PR in the release branch first-hand; understand what changed; decide where the risk is; and design the qualification that exercises the actual risk. Be the final voice before a release ships.
- Test Infrastructure at Scale: Build and evolve the test infrastructure - functional, integration, performance, and fault for the Inference Cloud platform. Plan for 20x growth in coverage, environments, and traffic. Today's setup will not survive tomorrow's load; design for the next horizon.
- End-to-End System Understanding: Reason through the full stack — client SDK, API, gateway, inference software, driver, hardware. Know enough to debug from any layer and to test the right thing.
- Code Review with Intent: Read and review developer PRs with genuine understanding of what each change does and what its blast radius is. Test the change's actual impact, not its surface area.
- Automation Expansion: Increase automation coverage continuously. Fix flaky tests rather than tolerate them. Use AI tooling effectively to accelerate test creation, debugging, and analysis.
- Quality Discipline: Choose high-value tests over volume metrics. Drive the team's standards for what \"tested\" means and what \"ready to ship\" means.
- Cross-Team Operation: Work with platform, ML, infrastructure, and product teams across timezones. Influence quality outcomes without owning every team's roadmap.
Skills & Qualifications
- 5+ years of experience in quality engineering, test engineering, or a closely related role, with substantial individual contributor experience on large-scale distributed systems or cloud infrastructure.
- Deep cloud platform experience, preferably AWS - networking, compute orchestration, container platforms, and multi-region production services. You can reason about what is happening at the cloud layer when something fails.
- Track record of building scalable test infrastructure - frameworks, harnesses, environments, and automation that scale with the system under test rather than fighting it.
- Strong systems debugging and reasoning. You can take an unfamiliar failure and follow it through layers of the stack to a root cause.
- Strong proficiency in at least one backend language (Python, Go, or C++), sufficient to read production code, write production-grade tests, and contribute infrastructure code directly.
- Excellent written and async communication. You operate effectively across time zones and in environments where most decisions get made in writing.
- Self-direction under ambiguity. You frame problems, make trade-off decisions, and push back when quality is at risk - without waiting to be asked.
- Experience with Cloud infrastructure, model serving systems, or GPU accelerated workloads is a strong plus.
- Experience using AI tooling (LLMs, coding assistants, agents) to accelerate test development, triage, or analysis is a plus.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n\nABOUT THE TEAM\n\nThe Cloud Quality team is responsible for the confidence behind every production release shipped to Cerebras Inference Cloud.\n\nWe work closely with platform, infrastructure, ML systems, and product engineering teams to ensure that rapid iteration never comes at the expense of customer trust. Our environment spans distributed cloud systems, multi-region deployments, APIs, orchestration layers, and hardware-backed inference services.\n\nWe are scaling quickly. The systems are growing in complexity, traffic is increasing rapidly, and release velocity remains high. We need engineers who can build quality systems that scale with the business.\n\n\n\nAbout the role\n\nWe are hiring a Cloud Quality Engineer to own the quality of our weekly cloud releases end to end and to build the test infrastructure that lets the team scale. This is a hands-on senior IC role for someone who treats quality as a first-class engineering problem - not a downstream gate.\n\nYou will drive every release from branch cut to sign-off, build scalable test infrastructure that grows with customer load, and push back when quality is at risk. You will operate effectively across timezones, async-first, with clear written communication.\n\nThis is a role for someone who self-drives. You will frequently work without complete product specifications, decide under ambiguity, and ask the right questions before code lands - not after.\n\n\n\nResponsibilities\n\n- Release Quality Ownership: Drive weekly cloud release qualification end to end. Read every PR in the release branch first-hand; understand what changed; decide where the risk is; and design the qualification that exercises the actual risk. Be the final voice before a release ships.\n\n- Test Infrastructure at Scale: Build and evolve the test infrastructure - functional, integration, performance, and fault for the Inference Cloud platform. Plan for 20x growth in coverage, environments, and traffic. Today's setup will not survive tomorrow's load; design for the next horizon.\n\n- End-to-End System Understanding: Reason through the full stack — client SDK, API, gateway, inference software, driver, hardware. Know enough to debug from any layer and to test the right thing.\n\n- Code Review with Intent: Read and review developer PRs with genuine understanding of what each change does and what its blast radius is. Test the change's actual impact, not its surface area.\n\n- Automation Expansion: Increase automation coverage continuously. Fix flaky tests rather than tolerate them. Use AI tooling effectively to accelerate test creation, debugging, and analysis.\n\n- Quality Discipline: Choose high-value tests over volume metrics. Drive the team's standards for what \"tested\" means and what \"ready to ship\" means.\n\n- Cross-Team Operation: Work with platform, ML, infrastructure, and product teams across timezones. Influence quality outcomes without owning every team's roadmap.\n\n\n\nSkills & Qualifications\n\n- 5+ years of experience in quality engineering, test engineering, or a closely related role, with substantial individual contributor experience on large-scale distributed systems or cloud infrastructure.\n\n- Deep cloud platform experience, preferably AWS - networking, compute orchestration, container platforms, and multi-region production services. You can reason about what is happening at the cloud layer when something fails.\n\n- Track record of building scalable test infrastructure - frameworks, harnesses, environments, and automation that scale with the system under test rather than fighting it.\n\n- Strong systems debugging and reasoning. You can take an unfamiliar failure and follow it through layers of the stack to a root cause.\n\n- Strong proficiency in at least one backend language (Python, Go, or C++), sufficient to read production code, write production-grade tests, and contribute infrastructure code directly.\n\n- Excellent written and async communication. You operate effectively across time zones and in environments where most decisions get made in writing.\n\n- Self-direction under ambiguity. You frame problems, make trade-off decisions, and push back when quality is at risk - without waiting to be asked.\n\n- Experience with Cloud infrastructure, model serving systems, or GPU accelerated workloads is a strong plus.\n\n- Experience using AI tooling (LLMs, coding assistants, agents) to accelerate test development, triage, or analysis is a plus.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"80775253-7fba-4a3b-87ee-0e70ce8e995c","title":"Software Engineer, Inference Platform ","department":"Software Engineering ","team":"Inference Service","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[{"location":"Toronto, CAN","address":{"postalAddress":{"postalCode":"M5H1Z5","addressRegion":"Ontario","streetAddress":"67 Richmond St W","addressCountry":"Canada","addressLocality":"Toronto"}}}],"publishedAt":"2026-06-20T01:28:09.918+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/80775253-7fba-4a3b-87ee-0e70ce8e995c","applyUrl":"https://jobs.ashbyhq.com/cerebras/80775253-7fba-4a3b-87ee-0e70ce8e995c/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About the Role
We're hiring a Software Engineer to help contribute to projects on our Inference Platform team. Our team primarily owns the orchestration layer that runs inference on our datacenter clusters, connecting cloud components with machine learning services. We are often the first team to face problems that haven't been solved yet, leading solutions across Kubernetes operators, service security policies, and CI/CD.
If you're interested in building the next-generation architecture of a globally distributed inference platform, we'd like to talk.
Responsibilities
Design, develop, test, and maintain production software, with responsibilities spanning testing, continuous development, observability, security, networking, debugging, and productionization.
Platform Direction. Help shape the technical direction for the Inference Platform, Kubernetes custom resource definitions, failure domains, service boundaries, and system evolution over time, and own the roadmap for major technical areas.
Reliability & Performance. Architect active-active systems with rapid failover, graceful degradation, and clear SLOs. Drive system-level improvements in latency, throughput, capacity efficiency, and resilience under unpredictable demand.
Execution on Critical Paths. Write and review production code in the most important parts of the platform. Make high-consequence architectural decisions within your area and set the technical bar through design reviews, code reviews, and sound engineering judgment.
Production Leadership. Lead on the hardest production issues and cross-system bottlenecks. Drive observability, incident response, capacity planning, and post-incident improvement with a high standard for operational rigor.
Technical Influence. Partner with ML, Product, Infrastructure, and Cloud teams to translate product and business requirements into scalable system designs, and drive alignment on shared technical decisions within your domain and adjacent platform surfaces.
Skills & Qualifications
3+ years of experience in software engineering, with experience building and operating large-scale distributed systems or cloud infrastructure.
Experience in distributed systems, ideally with Kubernetes.
Experience building highly available, latency-sensitive systems at scale.
Experience with security (certificates, TLS, mTLS).
Experience optimizing latency, throughput, and efficiency in high-QPS systems. Experience with TTFT and tail-latency reduction is a strong plus.
Strong proficiency in backend or systems languages such as Go or C++.
Preferred Skills & Qualifications
Experience with ML inference infrastructure, model serving systems, or GPU-accelerated workloads.
Location: Open to Sunnyvale or Toronto.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout the Role\n\nWe're hiring a Software Engineer to help contribute to projects on our Inference Platform team. Our team primarily owns the orchestration layer that runs inference on our datacenter clusters, connecting cloud components with machine learning services. We are often the first team to face problems that haven't been solved yet, leading solutions across Kubernetes operators, service security policies, and CI/CD.\n\nIf you're interested in building the next-generation architecture of a globally distributed inference platform, we'd like to talk.\n\nResponsibilities\n\n - Design, develop, test, and maintain production software, with responsibilities spanning testing, continuous development, observability, security, networking, debugging, and productionization.\n\n - Platform Direction. Help shape the technical direction for the Inference Platform, Kubernetes custom resource definitions, failure domains, service boundaries, and system evolution over time, and own the roadmap for major technical areas.\n\n - Reliability & Performance. Architect active-active systems with rapid failover, graceful degradation, and clear SLOs. Drive system-level improvements in latency, throughput, capacity efficiency, and resilience under unpredictable demand.\n\n - Execution on Critical Paths. Write and review production code in the most important parts of the platform. Make high-consequence architectural decisions within your area and set the technical bar through design reviews, code reviews, and sound engineering judgment.\n\n - Production Leadership. Lead on the hardest production issues and cross-system bottlenecks. Drive observability, incident response, capacity planning, and post-incident improvement with a high standard for operational rigor.\n\n - Technical Influence. Partner with ML, Product, Infrastructure, and Cloud teams to translate product and business requirements into scalable system designs, and drive alignment on shared technical decisions within your domain and adjacent platform surfaces.\n\nSkills & Qualifications\n\n - 3+ years of experience in software engineering, with experience building and operating large-scale distributed systems or cloud infrastructure.\n\n - Experience in distributed systems, ideally with Kubernetes.\n\n - Experience building highly available, latency-sensitive systems at scale.\n\n - Experience with security (certificates, TLS, mTLS).\n\n - Experience optimizing latency, throughput, and efficiency in high-QPS systems. Experience with TTFT and tail-latency reduction is a strong plus.\n\n - Strong proficiency in backend or systems languages such as Go or C++.\n\nPreferred Skills & Qualifications\n\n - Experience with ML inference infrastructure, model serving systems, or GPU-accelerated workloads.\n\nLocation: Open to Sunnyvale or Toronto.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"84a9df6b-fe96-4711-8106-971d829b6dc2","title":"Network Security Engineer (Remote)","department":"IT & Security","team":"Security","employmentType":"FullTime","location":"Remote (US)","secondaryLocations":[],"publishedAt":"2026-09-03T15:11:27.599+00:00","isListed":true,"isRemote":true,"workplaceType":"Remote","address":{"postalAddress":{"addressCountry":"United States"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/84a9df6b-fe96-4711-8106-971d829b6dc2","applyUrl":"https://jobs.ashbyhq.com/cerebras/84a9df6b-fe96-4711-8106-971d829b6dc2/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Cerebras is seeking a Network Security Engineer to build, operate, and secure the network infrastructure supporting our data centers, cloud environments, corporate network, and AI systems.
This is a remote, U.S.-based individual contributor role working across network security and network operations. You will support firewalls, segmentation, routing and switching, network access, and automation while collaborating with on-site data center and infrastructure teams. Occasional travel to Cerebras offices or data centers may be required.
Operate firewalls, ACLs, segmentation, and network security controls across data center, corporate, and AWS environments.
Remotely support data center network deployment, configuration, troubleshooting, maintenance, and lifecycle management in partnership with on-site teams.
Implement and maintain segmentation, firewall, and ACL policies across corporate, compute, customer, and infrastructure environments.
Manage inbound and outbound network controls, including public exposure, NAT, load balancers, DNS filtering, proxies, and egress policies.
Implement and operate VPN, ZTNA, NAC, Wi-Fi, and vendor or partner connectivity.
Perform recurring firewall rule reviews, segmentation audits, and remediation of unnecessary network exposure.
Automate network and security workflows using Terraform, Ansible, GitOps, Python, and policy as code.
Support network telemetry, detection, investigation, and containment in partnership with Security Operations.
Troubleshoot routing, switching, TCP/IP, DNS, TLS, and cloud networking issues.
Maintain network architecture documentation, procedures, and runbooks.
Coordinate remote changes and incident response across distributed infrastructure and engineering teams.
7+ years of experience in network security, network engineering, cloud security, or infrastructure security.
Strong hands-on experience with firewalls, ACLs, segmentation, routing, switching, VPNs, and network troubleshooting.
Experience supporting data center and on-premises network infrastructure, including working effectively with remote hands.
Experience with AWS networking, including VPCs, transit gateways, security groups, and load balancers.
Experience with Palo Alto, Juniper, Cloudflare, or similar platforms.
Proficiency with Terraform, Ansible, Python, GitOps, or similar automation tools.
Strong understanding of ZTNA, NAC, egress controls, TCP/IP, DNS, and TLS.
Strong written communication and documentation skills.
Ability to operate independently in a remote environment and collaborate across time zones.
Ability to travel occasionally to Cerebras offices or data centers as business needs require.
Experience in several of the following is valuable:
AI, HPC, or large-scale compute environments.
Data center networking and security.
AWS network security and segmentation.
ZTNA and VPN architectures.
DNS filtering, SWG, proxy, or SASE platforms.
Vendor and partner connectivity.
Public exposure and attack surface remediation.
Network detection and incident response.
Remote operation of geographically distributed network infrastructure.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nCerebras is seeking a Network Security Engineer to build, operate, and secure the network infrastructure supporting our data centers, cloud environments, corporate network, and AI systems.\n\nThis is a remote, U.S.-based individual contributor role working across network security and network operations. You will support firewalls, segmentation, routing and switching, network access, and automation while collaborating with on-site data center and infrastructure teams. Occasional travel to Cerebras offices or data centers may be required.\n\n\nRESPONSIBILITIES\n\n - Operate firewalls, ACLs, segmentation, and network security controls across data center, corporate, and AWS environments.\n\n - Remotely support data center network deployment, configuration, troubleshooting, maintenance, and lifecycle management in partnership with on-site teams.\n\n - Implement and maintain segmentation, firewall, and ACL policies across corporate, compute, customer, and infrastructure environments.\n\n - Manage inbound and outbound network controls, including public exposure, NAT, load balancers, DNS filtering, proxies, and egress policies.\n\n - Implement and operate VPN, ZTNA, NAC, Wi-Fi, and vendor or partner connectivity.\n\n - Perform recurring firewall rule reviews, segmentation audits, and remediation of unnecessary network exposure.\n\n - Automate network and security workflows using Terraform, Ansible, GitOps, Python, and policy as code.\n\n - Support network telemetry, detection, investigation, and containment in partnership with Security Operations.\n\n - Troubleshoot routing, switching, TCP/IP, DNS, TLS, and cloud networking issues.\n\n - Maintain network architecture documentation, procedures, and runbooks.\n\n - Coordinate remote changes and incident response across distributed infrastructure and engineering teams.\n\n\nSKILLS AND QUALIFICATIONS\n\n - 7+ years of experience in network security, network engineering, cloud security, or infrastructure security.\n\n - Strong hands-on experience with firewalls, ACLs, segmentation, routing, switching, VPNs, and network troubleshooting.\n\n - Experience supporting data center and on-premises network infrastructure, including working effectively with remote hands.\n\n - Experience with AWS networking, including VPCs, transit gateways, security groups, and load balancers.\n\n - Experience with Palo Alto, Juniper, Cloudflare, or similar platforms.\n\n - Proficiency with Terraform, Ansible, Python, GitOps, or similar automation tools.\n\n - Strong understanding of ZTNA, NAC, egress controls, TCP/IP, DNS, and TLS.\n\n - Strong written communication and documentation skills.\n\n - Ability to operate independently in a remote environment and collaborate across time zones.\n\n - Ability to travel occasionally to Cerebras offices or data centers as business needs require.\n\n\nRELEVANT EXPERIENCE\n\nExperience in several of the following is valuable:\n\n - AI, HPC, or large-scale compute environments.\n\n - Data center networking and security.\n\n - AWS network security and segmentation.\n\n - ZTNA and VPN architectures.\n\n - DNS filtering, SWG, proxy, or SASE platforms.\n\n - Vendor and partner connectivity.\n\n - Public exposure and attack surface remediation.\n\n - Network detection and incident response.\n\n - Remote operation of geographically distributed network infrastructure.\n\n \n \n\n\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"8b729a93-04bd-49da-8e87-5eb4ff3c8a26","title":"Principal Network Security Architect","department":"IT & Security","team":"Security","employmentType":"FullTime","location":"United States and Canada","secondaryLocations":[],"publishedAt":"2026-06-23T17:35:45.489+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":null,"jobUrl":"https://jobs.ashbyhq.com/cerebras/8b729a93-04bd-49da-8e87-5eb4ff3c8a26","applyUrl":"https://jobs.ashbyhq.com/cerebras/8b729a93-04bd-49da-8e87-5eb4ff3c8a26/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
We are seeking a Principal Network Security Architect to lead the design and evolution of the networks that connect Cerebras's data centers, offices, and cloud environments — the foundation that delivers the fastest AI inference on earth to customers like OpenAI and AWS. You will set the architectural direction for high-performance, resilient enterprise and data center networking, and partner closely with Site Reliability, Security, and Infrastructure to operate at the scale and speed our compute demands. The right candidate brings senior network design depth, a track record of building at hyperscale, and the judgment to balance performance, reliability, and security in a rapidly growing environment.
Responsibilities
Define and own the architectural roadmap for Cerebras's enterprise, data center, and cloud network estate.
Co-author secure design and lifecycle management of high-performance data center networking — including spine/leaf, RDMA, and high-bandwidth fabrics supporting wafer-scale compute.
Build and maintain an AI-agent based analysis and review framework for network changes as well as self-improvement driven by observed network patterns and use cases.
Partner with Network Security to deliver segmented, zero-trust-aligned network designs across data center and corporate environments.
Set standards for resiliency, observability, and capacity planning across the global network
Mentor engineers across regions (US, Canada, Bangalore, and beyond), and serve as the senior technical voice on cross-functional network initiatives.
Stay ahead of emerging networking patterns relevant to AI infrastructure and translate them into actionable architecture decisions.
Skills and Qualifications
10+ years of experience in enterprise and/or data center network engineering, including hands-on design and operations at scale.
Deep understanding in cloud networking and service mesh, with emphasis on K8s service mesh and virtual networks.
Deep expertise in routing, switching, and data center fabrics — including BGP, EVPN/VXLAN, and high-bandwidth/low-latency designs.
Hands-on experience with networking for high-performance compute or AI/ML workloads (RDMA, RoCE, InfiniBand exposure a plus).
Strong proficiency with network automation — infrastructure as code (Ansible, Terraform), version-controlled configuration, and CI/CD for network change.
Working knowledge of cloud networking (AWS preferred), including VPCs, transit gateways, Direct Connect, and hybrid connectivity patterns.
Experience operating networks at multi-site, global scale — including capacity planning, incident response, and vendor management.
Excellent written and verbal communication skills, with the ability to lead architecture conversations across technical and non-technical audiences.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nWe are seeking a Principal Network Security Architect to lead the design and evolution of the networks that connect Cerebras's data centers, offices, and cloud environments — the foundation that delivers the fastest AI inference on earth to customers like OpenAI and AWS. You will set the architectural direction for high-performance, resilient enterprise and data center networking, and partner closely with Site Reliability, Security, and Infrastructure to operate at the scale and speed our compute demands. The right candidate brings senior network design depth, a track record of building at hyperscale, and the judgment to balance performance, reliability, and security in a rapidly growing environment.\n\nResponsibilities\n\n - Define and own the architectural roadmap for Cerebras's enterprise, data center, and cloud network estate.\n\n - Co-author secure design and lifecycle management of high-performance data center networking — including spine/leaf, RDMA, and high-bandwidth fabrics supporting wafer-scale compute.\n\n - Build and maintain an AI-agent based analysis and review framework for network changes as well as self-improvement driven by observed network patterns and use cases.\n\n - Partner with Network Security to deliver segmented, zero-trust-aligned network designs across data center and corporate environments.\n\n - Set standards for resiliency, observability, and capacity planning across the global network\n\n - Mentor engineers across regions (US, Canada, Bangalore, and beyond), and serve as the senior technical voice on cross-functional network initiatives.\n\n - Stay ahead of emerging networking patterns relevant to AI infrastructure and translate them into actionable architecture decisions.\n\nSkills and Qualifications\n\n - 10+ years of experience in enterprise and/or data center network engineering, including hands-on design and operations at scale.\n\n - Deep understanding in cloud networking and service mesh, with emphasis on K8s service mesh and virtual networks.\n\n - Deep expertise in routing, switching, and data center fabrics — including BGP, EVPN/VXLAN, and high-bandwidth/low-latency designs.\n\n - Hands-on experience with networking for high-performance compute or AI/ML workloads (RDMA, RoCE, InfiniBand exposure a plus).\n\n - Strong proficiency with network automation — infrastructure as code (Ansible, Terraform), version-controlled configuration, and CI/CD for network change.\n\n - Working knowledge of cloud networking (AWS preferred), including VPCs, transit gateways, Direct Connect, and hybrid connectivity patterns.\n\n - Experience operating networks at multi-site, global scale — including capacity planning, incident response, and vendor management.\n\n - Excellent written and verbal communication skills, with the ability to lead architecture conversations across technical and non-technical audiences.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"dbeeb53b-1bfd-4454-8285-4ec5dbceebc3","title":"Principal AI Security Engineer","department":"IT & Security","team":"Security","employmentType":"FullTime","location":"United States and Canada","secondaryLocations":[],"publishedAt":"2026-06-23T17:39:01.800+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":null,"jobUrl":"https://jobs.ashbyhq.com/cerebras/dbeeb53b-1bfd-4454-8285-4ec5dbceebc3","applyUrl":"https://jobs.ashbyhq.com/cerebras/dbeeb53b-1bfd-4454-8285-4ec5dbceebc3/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Cerebras is seeking a Principal AI Security Engineer to lead hands-on security engineering for enterprise IT, infrastructure, AI platforms, and agentic systems.
In this role, you will design and build security controls for systems that support training, inference, model serving, customer workloads, internal automation, and AI-assisted development. You will work across product, cloud, infrastructure, identity, runtime, data, and developer platforms to protect sensitive data, enterprise and customer environments, models, tools, agents, and control planes.
This is a principal IC role for someone who can turn ambiguous AI and platform security risks into practical architecture, reusable controls, and production-ready systems that teams can adopt by default.
Define security architecture and build controls for AI platforms, training and inference workflows, model-serving systems, customer workloads, developer workflows, and agentic
Develop reusable AI and agent security patterns for identity, authorization, delegated authority, scoped tool access, MCPs, connectors, secrets, approvals, isolation, auditability, and
Design runtime controls that constrain execution, access, data exposure, model and tool interaction, and blast radius.
Build security capabilities as code using infrastructure as code, configuration as code, policy as code, GitOps, CI/CD, and automated validation.
Define secure development patterns for AI systems, agents, prompts, tools, models, policies, evaluations, releases, and rollback.
Automate security reviews, policy checks, evidence collection, control validation, and remediation
Instrument AI, agent, and platform activity with telemetry, traceability, policy decisions, audit logs, anomaly signals, and response workflows.
Lead hands-on security reviews and influence product, platform, infrastructure, and security architecture through practical design changes and reusable controls.
10+ years of experience in security engineering, platform security, infrastructure security, product security, or related technical security roles.
Strong hands-on engineering ability in Python and at least one additional production
Experience designing, building, operating, and improving security controls as
Strong cloud and infrastructure security experience, preferably with AWS, including IAM, networking, secrets management, logging, and cloud-native control planes.
Deep understanding of identity and access systems, including SSO, MFA, OAuth, service accounts, workload identity, authorization, privileged access, and least privilege.
Practical experience securing runtime environments such as containers, Kubernetes, isolated workloads, secure development environments, distributed compute platforms, or production service infrastructure.
Familiarity with AI security, LLM application security, agentic workflows, MCPs, prompt injection, autonomous coding agents, or AI platform security.
Ability to reason about cross-system risk involving identity, data, models, tools, networks, workflows, approvals, and automation.
Strong written communication skills and the ability to influence senior technical stakeholders across Security, Product, IT, Infrastructure, and Engineering.
We do not expect every candidate to have worked across all of these areas, but we value depth in several:
AI, ML, training, inference, model-serving, or large-scale compute
Coding agents, agent platforms, MCP servers, internal developer platforms, or AI-assisted development environments.
Workload identity, secrets brokers, token brokers, short-lived credentials, privileged access, or zero-standing-privilege architectures.
Policy-as-code, authorization services, runtime enforcement layers, or security control
Software delivery security, including source control, CI/CD, build systems, artifacts, provenance, signing, and release gates.
Detection, investigation, and response workflows for cloud, infrastructure, identity, AI, or agent
Success in this role means shaping how Cerebras secures the systems behind AI training, inference, model serving, customer workloads, and agentic automation. You will turn emerging AI and agent risks into reusable security architecture, safer identity and authorization models, scoped tool access, runtime containment, secure software delivery paths, automated policy validation, high-signal telemetry, and controls that engineering teams can adopt by default.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n\nABOUT THE ROLE\n\nCerebras is seeking a Principal AI Security Engineer to lead hands-on security engineering for enterprise IT, infrastructure, AI platforms, and agentic systems.\n\nIn this role, you will design and build security controls for systems that support training, inference, model serving, customer workloads, internal automation, and AI-assisted development. You will work across product, cloud, infrastructure, identity, runtime, data, and developer platforms to protect sensitive data, enterprise and customer environments, models, tools, agents, and control planes.\n\nThis is a principal IC role for someone who can turn ambiguous AI and platform security risks into practical architecture, reusable controls, and production-ready systems that teams can adopt by default.\n\n\nRESPONSIBILITIES\n\n - Define security architecture and build controls for AI platforms, training and inference workflows, model-serving systems, customer workloads, developer workflows, and agentic\n\n - Develop reusable AI and agent security patterns for identity, authorization, delegated authority, scoped tool access, MCPs, connectors, secrets, approvals, isolation, auditability, and\n\n - Design runtime controls that constrain execution, access, data exposure, model and tool interaction, and blast radius.\n\n - Build security capabilities as code using infrastructure as code, configuration as code, policy as code, GitOps, CI/CD, and automated validation.\n\n - Define secure development patterns for AI systems, agents, prompts, tools, models, policies, evaluations, releases, and rollback.\n\n - Automate security reviews, policy checks, evidence collection, control validation, and remediation\n\n - Instrument AI, agent, and platform activity with telemetry, traceability, policy decisions, audit logs, anomaly signals, and response workflows.\n\n - Lead hands-on security reviews and influence product, platform, infrastructure, and security architecture through practical design changes and reusable controls.\n\n\nSKILLS AND QUALIFICATIONS\n\n - 10+ years of experience in security engineering, platform security, infrastructure security, product security, or related technical security roles.\n\n - Strong hands-on engineering ability in Python and at least one additional production\n\n - Experience designing, building, operating, and improving security controls as\n\n - Strong cloud and infrastructure security experience, preferably with AWS, including IAM, networking, secrets management, logging, and cloud-native control planes.\n\n - Deep understanding of identity and access systems, including SSO, MFA, OAuth, service accounts, workload identity, authorization, privileged access, and least privilege.\n\n - Practical experience securing runtime environments such as containers, Kubernetes, isolated workloads, secure development environments, distributed compute platforms, or production service infrastructure.\n\n - Familiarity with AI security, LLM application security, agentic workflows, MCPs, prompt injection, autonomous coding agents, or AI platform security.\n\n - Ability to reason about cross-system risk involving identity, data, models, tools, networks, workflows, approvals, and automation.\n\n - Strong written communication skills and the ability to influence senior technical stakeholders across Security, Product, IT, Infrastructure, and Engineering.\n\n\nRELEVANT EXPERIENCE\n\nWe do not expect every candidate to have worked across all of these areas, but we value depth in several:\n\n - AI, ML, training, inference, model-serving, or large-scale compute\n\n - Coding agents, agent platforms, MCP servers, internal developer platforms, or AI-assisted development environments.\n\n - Workload identity, secrets brokers, token brokers, short-lived credentials, privileged access, or zero-standing-privilege architectures.\n\n - Policy-as-code, authorization services, runtime enforcement layers, or security control\n\n - Software delivery security, including source control, CI/CD, build systems, artifacts, provenance, signing, and release gates.\n\n - Detection, investigation, and response workflows for cloud, infrastructure, identity, AI, or agent\n\n\nWHAT SUCCESS LOOKS LIKE\n\nSuccess in this role means shaping how Cerebras secures the systems behind AI training, inference, model serving, customer workloads, and agentic automation. You will turn emerging AI and agent risks into reusable security architecture, safer identity and authorization models, scoped tool access, runtime containment, secure software delivery paths, automated policy validation, high-signal telemetry, and controls that engineering teams can adopt by default.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"cf45f13c-b6a9-4df2-b6c3-eefea14a024f","title":"Inference ML API SDET","department":"Software Engineering ","team":"Inference Service","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[{"location":"Toronto, CAN","address":{"postalAddress":{"postalCode":"M5H1Z5","addressRegion":"Ontario","streetAddress":"67 Richmond St W","addressCountry":"Canada","addressLocality":"Toronto"}}}],"publishedAt":"2026-06-29T15:37:31.221+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/cf45f13c-b6a9-4df2-b6c3-eefea14a024f","applyUrl":"https://jobs.ashbyhq.com/cerebras/cf45f13c-b6a9-4df2-b6c3-eefea14a024f/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Team
The ML API Quality team is responsible for the confidence behind every production release shipped to Cerebras Inference Cloud. We work closely with platform, infrastructure, ML systems, and product engineering teams to ensure that rapid iteration never comes at the expense of customer trust. Our environment spans distributed cloud systems, multi-region deployments, APIs, orchestration layers, and hardware-backed inference services.
We are scaling quickly. The systems are growing in complexity, traffic is increasing rapidly, and release velocity remains high. We need engineers who can build quality systems that scale with the business.
About The Role
As a Senior Software Engineer in Test for the ML API features team, you will lead testing strategy and execution for AI/ML models, evaluating accuracy, fairness, and performance at scale. You will serve as a key technical leader in delivering and validating all software and hardware components for Cerebras API Features. You will own software components feature integration quality and drive pre-deployment and production validation for Cerebras inference solutions. In this role, you will define and champion best testing practices, establish robust debugging methodologies, and mentor junior engineers while advocating for world-class product quality.
Responsibilities
Architect and own end-to-end test strategies for new features, developing scalable tests, frameworks, and tooling to ensure quality.
Lead contributions to industry-standard benchmarks and drive adoption of rigorous evaluation methodologies.
Define and drive automation initiatives to significantly improve internal engineering efficiency and test coverage.
Make strategic decisions around coverage trade-offs, resource requirements, and risk-based testing priorities.
Serve as a technical anchor in a highly agile environment, adapting quickly to shifting priorities while maintaining quality standards.
Mentor and guide junior SDETs on testing methodology, debugging practices, and automation development.
Proactively identify systemic quality gaps and drive cross-functional initiatives to address them.
Lead and facilitate effective technical communication across teams and time zones.
Skills & Qualifications
5+ years of relevant industry experience in software integration, development, or quality engineering.
Deep expertise in automation and programming using one or more languages such as Python, C++, or Go; ability to design and build reusable test frameworks from the ground up.
Proven experience testing compute, machine learning, networking, or storage systems within large-scale enterprise environments.
Strong track record of debugging complex issues across distributed, scaled-out deployments.
Demonstrated ability to lead cross-functional quality initiatives involving product development, product management, customer operations, and field teams.
Excellent verbal and written communication skills, with experience presenting technical findings to both engineering and leadership audiences.
Strong organizational skills, ownership mindset, and ability to drive projects to completion independently.
Experience leading and mentoring engineers across geographically dispersed teams and time zones.
Preferred Skills & Qualifications
Hands-on experience with ML workloads including LLM and/or multimodal training or inference.
Deep familiarity with hardware architecture, performance optimizations, compilers, and ML frameworks.
Experience designing test strategies for distributed systems, cloud infrastructure, and security validation.
Experience with microservices deployment, debugging, and orchestration at scale.
Prior experience owning or significantly contributing to a team's quality engineering culture or test infrastructure.
Location
This role follows a hybrid schedule, requiring in-office presence 3 days per week. Fully remote is not an option.
Office locations: Sunnyvale, CA | Toronto, Canada
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Team\n\nThe ML API Quality team is responsible for the confidence behind every production release shipped to Cerebras Inference Cloud. We work closely with platform, infrastructure, ML systems, and product engineering teams to ensure that rapid iteration never comes at the expense of customer trust. Our environment spans distributed cloud systems, multi-region deployments, APIs, orchestration layers, and hardware-backed inference services.\n\nWe are scaling quickly. The systems are growing in complexity, traffic is increasing rapidly, and release velocity remains high. We need engineers who can build quality systems that scale with the business.\n\nAbout The Role\n\nAs a Senior Software Engineer in Test for the ML API features team, you will lead testing strategy and execution for AI/ML models, evaluating accuracy, fairness, and performance at scale. You will serve as a key technical leader in delivering and validating all software and hardware components for Cerebras API Features. You will own software components feature integration quality and drive pre-deployment and production validation for Cerebras inference solutions. In this role, you will define and champion best testing practices, establish robust debugging methodologies, and mentor junior engineers while advocating for world-class product quality.\n\nResponsibilities\n\n - Architect and own end-to-end test strategies for new features, developing scalable tests, frameworks, and tooling to ensure quality.\n\n - Lead contributions to industry-standard benchmarks and drive adoption of rigorous evaluation methodologies.\n\n - Define and drive automation initiatives to significantly improve internal engineering efficiency and test coverage.\n\n - Make strategic decisions around coverage trade-offs, resource requirements, and risk-based testing priorities.\n\n - Serve as a technical anchor in a highly agile environment, adapting quickly to shifting priorities while maintaining quality standards.\n\n - Mentor and guide junior SDETs on testing methodology, debugging practices, and automation development.\n\n - Proactively identify systemic quality gaps and drive cross-functional initiatives to address them.\n\n - Lead and facilitate effective technical communication across teams and time zones.\n\nSkills & Qualifications\n\n - 5+ years of relevant industry experience in software integration, development, or quality engineering.\n\n - Deep expertise in automation and programming using one or more languages such as Python, C++, or Go; ability to design and build reusable test frameworks from the ground up.\n\n - Proven experience testing compute, machine learning, networking, or storage systems within large-scale enterprise environments.\n\n - Strong track record of debugging complex issues across distributed, scaled-out deployments.\n\n - Demonstrated ability to lead cross-functional quality initiatives involving product development, product management, customer operations, and field teams.\n\n - Excellent verbal and written communication skills, with experience presenting technical findings to both engineering and leadership audiences.\n\n - Strong organizational skills, ownership mindset, and ability to drive projects to completion independently.\n\n - Experience leading and mentoring engineers across geographically dispersed teams and time zones.\n\nPreferred Skills & Qualifications\n\n - Hands-on experience with ML workloads including LLM and/or multimodal training or inference.\n\n - Deep familiarity with hardware architecture, performance optimizations, compilers, and ML frameworks.\n\n - Experience designing test strategies for distributed systems, cloud infrastructure, and security validation.\n\n - Experience with microservices deployment, debugging, and orchestration at scale.\n\n - Prior experience owning or significantly contributing to a team's quality engineering culture or test infrastructure.\n\nLocation\n\nThis role follows a hybrid schedule, requiring in-office presence 3 days per week. Fully remote is not an option.\n\nOffice locations: Sunnyvale, CA | Toronto, Canada\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"691225e6-aff8-4371-968d-5aa0b5d8637b","title":"Sr./Staff TPM - Inference Capacity","department":"Software Engineering ","team":"Inference Service","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[{"location":"Remote","address":null},{"location":"Toronto, CAN","address":{"postalAddress":{"postalCode":"M5H1Z5","addressRegion":"Ontario","streetAddress":"67 Richmond St W","addressCountry":"Canada","addressLocality":"Toronto"}}}],"publishedAt":"2026-06-29T20:50:26.407+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/691225e6-aff8-4371-968d-5aa0b5d8637b","applyUrl":"https://jobs.ashbyhq.com/cerebras/691225e6-aff8-4371-968d-5aa0b5d8637b/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
As demand for AI continues to accelerate, intelligent capacity management becomes one of the company's most strategic challenges. Every customer commitment, model launch, and infrastructure investment depends on making the right capacity decisions at the right time.
We're looking for an experienced Technical Program Manager to lead capacity planning and fleet strategy for our Inference Service organization. This is a highly visible role working directly with Engineering, Product, Infrastructure, SRE, Operations, and executive leadership to maximize utilization of one of the world's most advanced AI inference fleets.
Capacity planning and forecasting. Build and maintain the 6 / 12 / 26-week rolling capacity model across every cluster. Work with product team to translate customer contracts and sales pipeline asks into capacity requirements. Forecast model replicas, system-hours, and spares by customer and by model. Reconcile against actuals weekly. Maintain the source-of-truth doc.
New Datacenter Capacity bring-up. Collaborate with datacenter infrastructure and operations teams to support new datacenter bringup and ensure production readiness. Drive engineering efforts and related automation to ensure on-time and quality delivery.
Allocation and cluster placement. Partner closely with the SRE and product team to run the weekly capacity review across different customers/models/clusters. Decide model placement and re-balancing: which customer tenants land where, which clusters absorb new launches, which freezes are in effect etc. Run the weekly capacity and utilization report for the Inference Service leadership. Post capacity allocation, drive downstream tasks w.r.t deploying models across the allocated capacity with SRE team.
Drive capacity planning tool adoption. Partner with console engineering team to drive stakeholder adoption of the inhouse built capacity planning and allocation tool, including user acceptance testing, issue resolution, tracking changes, pilot testing and deployment. In general, Contribute to the continuous process improvement and development of internal capacity management tools.
Incident tracking and postmortems. Proactively identify and mitigate capacity bottlenecks, risks, and dependencies. In case of any SLA drop due to capacity misallocations, drive related resolution and postmortem.
Run weekly capacity planning and daily capacity and deployment tracking with Engineering, product and operations team. Own fleet utilization reporting and forecasting
Drive capacity planning for new customer deployments and major model launches
Drive continuous improvement and stakeholder adoption of new capacity management platform
Drive org level strategic initiatives related to capacity expansion, improving fleet efficiency and maximizing effective utilization of available systems
Lead planning around major infrastructure events including but not limited to new customer commits, new model releases, change to DC/cluster architecture, etc. that impacts capacity and fleet utilization. Update capacity plans and forecasts accordingly.
Maintain Jira EPICs and Confluence pages related to capacity planning, reporting and change management to ensure execution transparency across teams
5+ years of TPM, technical program management, or product operations experience in cloud infrastructure, large-scale ML serving, or hyperscaler capacity planning
Experience leading large cross-functional programs involving Engineering, Product, and Operations
Comfort with the inference serving stack: model replicas, batching, prefill/decode, KV cache, accelerator scheduling
Strong data fluency: SQL, Grafana, basic Python or Flux to pull your own numbers without waiting for an analyst
Track record of running a recurring cross-functional ritual involving senior engineers and LT
Direct experience with AI accelerator fleet operations such as Habana, TPU pods, Inferentia, Trainium
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n\nABOUT THE ROLE\n\nAs demand for AI continues to accelerate, intelligent capacity management becomes one of the company's most strategic challenges. Every customer commitment, model launch, and infrastructure investment depends on making the right capacity decisions at the right time. \n\nWe're looking for an experienced Technical Program Manager to lead capacity planning and fleet strategy for our Inference Service organization. This is a highly visible role working directly with Engineering, Product, Infrastructure, SRE, Operations, and executive leadership to maximize utilization of one of the world's most advanced AI inference fleets. \n\n \n\n\nWHAT YOU'LL OWN\n\nCapacity planning and forecasting. Build and maintain the 6 / 12 / 26-week rolling capacity model across every cluster. Work with product team to translate customer contracts and sales pipeline asks into capacity requirements. Forecast model replicas, system-hours, and spares by customer and by model. Reconcile against actuals weekly. Maintain the source-of-truth doc. \n\nNew Datacenter Capacity bring-up. Collaborate with datacenter infrastructure and operations teams to support new datacenter bringup and ensure production readiness. Drive engineering efforts and related automation to ensure on-time and quality delivery. \n\nAllocation and cluster placement. Partner closely with the SRE and product team to run the weekly capacity review across different customers/models/clusters. Decide model placement and re-balancing: which customer tenants land where, which clusters absorb new launches, which freezes are in effect etc. Run the weekly capacity and utilization report for the Inference Service leadership. Post capacity allocation, drive downstream tasks w.r.t deploying models across the allocated capacity with SRE team. \n\nDrive capacity planning tool adoption. Partner with console engineering team to drive stakeholder adoption of the inhouse built capacity planning and allocation tool, including user acceptance testing, issue resolution, tracking changes, pilot testing and deployment. In general, Contribute to the continuous process improvement and development of internal capacity management tools. \n\nIncident tracking and postmortems. Proactively identify and mitigate capacity bottlenecks, risks, and dependencies. In case of any SLA drop due to capacity misallocations, drive related resolution and postmortem. \n\n\n\nKEY RESPONSIBILITIES\n\n - Run weekly capacity planning and daily capacity and deployment tracking with Engineering, product and operations team. Own fleet utilization reporting and forecasting\n\n - Drive capacity planning for new customer deployments and major model launches\n\n - Drive continuous improvement and stakeholder adoption of new capacity management platform\n\n - Drive org level strategic initiatives related to capacity expansion, improving fleet efficiency and maximizing effective utilization of available systems\n\n - Lead planning around major infrastructure events including but not limited to new customer commits, new model releases, change to DC/cluster architecture, etc. that impacts capacity and fleet utilization. Update capacity plans and forecasts accordingly.\n\n - Maintain Jira EPICs and Confluence pages related to capacity planning, reporting and change management to ensure execution transparency across teams\n\n\nQUALIFICATIONS\n\n - 5+ years of TPM, technical program management, or product operations experience in cloud infrastructure, large-scale ML serving, or hyperscaler capacity planning\n\n - Experience leading large cross-functional programs involving Engineering, Product, and Operations\n\n - Comfort with the inference serving stack: model replicas, batching, prefill/decode, KV cache, accelerator scheduling\n\n - Strong data fluency: SQL, Grafana, basic Python or Flux to pull your own numbers without waiting for an analyst\n\n - Track record of running a recurring cross-functional ritual involving senior engineers and LT\n\n - Direct experience with AI accelerator fleet operations such as Habana, TPU pods, Inferentia, Trainium\n\n \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"62b9ff34-0fcb-414d-ba1f-cf05edd4b164","title":"Regional Data Center Manager - Finland","department":"Datacenters","team":"Datacenters","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2026-06-29T18:51:46.793+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressRegion":"California ","addressCountry":"United States","addressLocality":"Sunnyvale "}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/62b9ff34-0fcb-414d-ba1f-cf05edd4b164","applyUrl":"https://jobs.ashbyhq.com/cerebras/62b9ff34-0fcb-414d-ba1f-cf05edd4b164/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Regional Data Center Manager – Finland (Bilingual Required)
Location
Mikkeli (South Savo) Area, Finland (with regional travel)
About The Role
Cerebras Systems is seeking a Regional Data Center Manager to lead operations, deployment execution, and infrastructure performance across our Finland-based and broader European deployments.
This role sits within the AI Infrastructure organization and is responsible for ensuring that high-density AI clusters are built rapidly, operated reliably, and scaled efficiently.
This is a hands-on leadership role requiring:
Practical data center experience.
Strong working knowledge of MEP systems (Mechanical, Electrical, Plumbing).
The ability to interface directly with facility providers;
The ability to execute at a managerial level, leading local teams while translating and enforcing requirements from global HQ engineering and operations teams.
Fluency in both Finnish and English is required. Being conversant in French is highly desirable.
Own end-to-end data center operations across Finland and adjacent EU sites.
Ensure infrastructure meets performance, uptime, and safety requirements.
Act as the regional execution owner, translating HQ standards into site-level implementation.
Lead incident response and escalation for facility and infrastructure issues.
Serve as primary interface with facility providers, landlords, and MEP vendors.
Ensure facilities meet Cerebras requirements across:
Power (UPS, transformers, distribution paths);
Cooling (CDUs, chilled water loops, CRAH/CRAC systems);
Plumbing (flow, pressure, and loop stability).
Validate facility readiness and performance using real-time telemetry (flow rate, temperature, pressure).
Lead regional execution of cluster deployments (5MW modular increments)
Coordinate with global teams to execute:
Site readiness;
Equipment installation;
Commissioning and handoff to operations.
Drive cross-functional alignment between:
Site Operations;
Network Operations;
Cluster Operations.
Manage and develop local data center technicians and site staff.
Ensure local execution aligns with global standards, MoPs, and engineering requirements.
Act as the bridge between HQ and the field, ensuring:
Requirements are clearly communicated;
Execution is consistent and timely.
Required
Bilingual fluency in Finnish and English; French fluency desirable.
5–10+ years of practical data center or critical facility experience.
Strong working knowledge of MEP systems (mechanical, electrical, plumbing).
Proven ability to interface directly with facility providers and vendors.
Experience managing or leading site-level technical teams.
Ability to execute operationally while aligning with centralized/global direction.
Preferred
Experience with high-density or liquid-cooled environments.
Exposure to AI/HPC infrastructure.
Experience in multi-site or regional operations.
Familiarity with structured incident management frameworks (e.g., ITIL).
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nRegional Data Center Manager – Finland (Bilingual Required)\n\nLocation\nMikkeli (South Savo) Area, Finland (with regional travel)\n\nAbout The Role\nCerebras Systems is seeking a Regional Data Center Manager to lead operations, deployment execution, and infrastructure performance across our Finland-based and broader European deployments.\n\nThis role sits within the AI Infrastructure organization and is responsible for ensuring that high-density AI clusters are built rapidly, operated reliably, and scaled efficiently.\n\nThis is a hands-on leadership role requiring:\n\n - Practical data center experience.\n\n - Strong working knowledge of MEP systems (Mechanical, Electrical, Plumbing).\n\n - The ability to interface directly with facility providers;\n \n - The ability to execute at a managerial level, leading local teams while translating and enforcing requirements from global HQ engineering and operations teams.\n\n - Fluency in both Finnish and English is required. Being conversant in French is highly desirable.\n \n\n\nKEY RESPONSIBILITIES\nREGIONAL OPERATIONS & EXECUTION\n\n - Own end-to-end data center operations across Finland and adjacent EU sites.\n\n - Ensure infrastructure meets performance, uptime, and safety requirements.\n\n - Act as the regional execution owner, translating HQ standards into site-level implementation.\n\n - Lead incident response and escalation for facility and infrastructure issues.\n\n\nFACILITY INTERFACE & MEP OVERSIGHT\n\n - Serve as primary interface with facility providers, landlords, and MEP vendors.\n\n - Ensure facilities meet Cerebras requirements across:\n \n - Power (UPS, transformers, distribution paths);\n \n - Cooling (CDUs, chilled water loops, CRAH/CRAC systems);\n \n - Plumbing (flow, pressure, and loop stability).\n\n - Validate facility readiness and performance using real-time telemetry (flow rate, temperature, pressure).\n\n\nBUILD & DEPLOYMENT LEADERSHIP\n\n - Lead regional execution of cluster deployments (5MW modular increments)\n\n - Coordinate with global teams to execute:\n \n - Site readiness;\n \n - Equipment installation;\n \n - Commissioning and handoff to operations.\n\n - Drive cross-functional alignment between:\n \n - Site Operations;\n \n - Network Operations;\n \n - Cluster Operations.\n\n\nTEAM LEADERSHIP & HQ ALIGNMENT\n\n - Manage and develop local data center technicians and site staff.\n\n - Ensure local execution aligns with global standards, MoPs, and engineering requirements.\n\n - Act as the bridge between HQ and the field, ensuring:\n \n - Requirements are clearly communicated;\n \n - Execution is consistent and timely.\n\n\nQUALIFICATIONS\n\nRequired\n\n - Bilingual fluency in Finnish and English; French fluency desirable.\n\n - 5–10+ years of practical data center or critical facility experience.\n\n - Strong working knowledge of MEP systems (mechanical, electrical, plumbing).\n\n - Proven ability to interface directly with facility providers and vendors.\n\n - Experience managing or leading site-level technical teams.\n\n - Ability to execute operationally while aligning with centralized/global direction.\n\nPreferred\n\n - Experience with high-density or liquid-cooled environments.\n\n - Exposure to AI/HPC infrastructure.\n\n - Experience in multi-site or regional operations.\n\n - Familiarity with structured incident management frameworks (e.g., ITIL).\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"c2d428d4-b32d-46e8-ae5d-37fe54fb9bf7","title":"Regional Data Center Manager - Western Canada","department":"Datacenters","team":"Datacenters","employmentType":"FullTime","location":"Vancouver, CAN","secondaryLocations":[],"publishedAt":"2026-06-29T19:01:00.641+00:00","isListed":true,"isRemote":true,"workplaceType":"Remote","address":{"postalAddress":{"addressRegion":"British Columbia ","addressCountry":"Canada","addressLocality":"Vancouver"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/c2d428d4-b32d-46e8-ae5d-37fe54fb9bf7","applyUrl":"https://jobs.ashbyhq.com/cerebras/c2d428d4-b32d-46e8-ae5d-37fe54fb9bf7/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Regional Data Center Manager – Western Canada
Location
Calgary, Edmonton or Vancouver, BC (regional travel required).
About The Role
Cerebras Systems is seeking a Regional Data Center Manager to lead infrastructure operations and deployment execution across Western Canada.
This role is responsible for ensuring that AI infrastructure is delivered, operated, and scaled effectively, while maintaining strong alignment with global engineering and operations teams.
This is a field-oriented leadership role requiring:
Hands-on data center experience.
Solid understanding of MEP systems.
Direct engagement with facility providers.
The ability to manage local teams while executing HQ-driven requirements.
Lead day-to-day operations across Western Canada sites.
Ensure infrastructure meets uptime, performance, and reliability targets.
Own incident response coordination for facility-related issues.
Maintain alignment with global:
Cluster Operations;
Network Operations;
Platform Engineering.
Act as primary interface with facility operators and vendors.
Ensure site infrastructure supports:
High-density compute loads;
Liquid cooling systems;
Redundant power architectures;
Validate facility performance against defined operational thresholds.
Execute modular deployments (5MW increments).
Lead coordination of:
Site readiness;
Equipment install;
Commissioning and operational handoff.
Support scaling toward multi-site, high-capacity regional footprint.
Lead and develop local data center technicians and engineers.
Ensure execution aligns with HQ-defined standards, procedures, and timelines.
Serve as the operational bridge between HQ and field teams.
Required
5–10+ years of data center or critical facility experience.
Working knowledge of MEP systems (mechanical, electrical, plumbing).
Experience interfacing with facility providers and vendors.
Demonstrated ability to lead site-level teams.
Ability to execute both operationally and managerially in a fast-paced environment.
Preferred
Experience with AI/HPC infrastructure.
Exposure to liquid cooling systems.
Experience operating in cold-weather environments.
Familiarity with structured incident management frameworks.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nRegional Data Center Manager – Western Canada\n\nLocation\nCalgary, Edmonton or Vancouver, BC (regional travel required). \n\n\nAbout The Role\nCerebras Systems is seeking a Regional Data Center Manager to lead infrastructure operations and deployment execution across Western Canada.\n\n\nThis role is responsible for ensuring that AI infrastructure is delivered, operated, and scaled effectively, while maintaining strong alignment with global engineering and operations teams.\n\n\nThis is a field-oriented leadership role requiring:\n\n - Hands-on data center experience.\n\n - Solid understanding of MEP systems.\n\n - Direct engagement with facility providers.\n\n - The ability to manage local teams while executing HQ-driven requirements.\n \n\n\nKEY RESPONSIBILITIES\nREGIONAL OPERATIONS OWNERSHIP\n\n - Lead day-to-day operations across Western Canada sites.\n\n - Ensure infrastructure meets uptime, performance, and reliability targets.\n\n - Own incident response coordination for facility-related issues.\n\n - Maintain alignment with global:\n \n - Cluster Operations;\n \n - Network Operations;\n \n - Platform Engineering.\n\n\nFACILITY INTERFACE & INFRASTRUCTURE OVERSIGHT\n\n - Act as primary interface with facility operators and vendors.\n\n - Ensure site infrastructure supports:\n \n - High-density compute loads;\n \n - Liquid cooling systems;\n \n - Redundant power architectures;\n \n - Validate facility performance against defined operational thresholds.\n\n\nDEPLOYMENT & BUILD EXECUTION\n\n - Execute modular deployments (5MW increments).\n\n - Lead coordination of:\n \n - Site readiness;\n \n - Equipment install;\n \n - Commissioning and operational handoff.\n\n - Support scaling toward multi-site, high-capacity regional footprint.\n\n\nTEAM LEADERSHIP & HQ ALIGNMENT\n\n - Lead and develop local data center technicians and engineers.\n\n - Ensure execution aligns with HQ-defined standards, procedures, and timelines.\n\n - Serve as the operational bridge between HQ and field teams.\n\n\nQUALIFICATIONS\n\nRequired\n\n - 5–10+ years of data center or critical facility experience.\n\n - Working knowledge of MEP systems (mechanical, electrical, plumbing).\n\n - Experience interfacing with facility providers and vendors.\n\n - Demonstrated ability to lead site-level teams.\n\n - Ability to execute both operationally and managerially in a fast-paced environment.\n\nPreferred\n\n - Experience with AI/HPC infrastructure.\n\n - Exposure to liquid cooling systems.\n\n - Experience operating in cold-weather environments.\n\n - Familiarity with structured incident management frameworks.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"20010f8f-5ede-469a-b432-c38dc223e11c","title":"Manufacturing Automation Engineer","department":"Hardware","team":"Manufacturing","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2026-06-30T22:07:02.864+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressRegion":"California ","addressCountry":"United States","addressLocality":"Sunnyvale "}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/20010f8f-5ede-469a-b432-c38dc223e11c","applyUrl":"https://jobs.ashbyhq.com/cerebras/20010f8f-5ede-469a-b432-c38dc223e11c/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Job Summary
We are seeking a skilled and motivated Manufacturing Automation Engineer to design, implement, maintain, and optimize automated manufacturing assembly and test systems. The ideal candidate will collaborate with cross-functional teams to improve production efficiency, enhance product quality, reduce downtime, and support continuous improvement initiatives through advanced automation technologies.
Key Responsibilities
Design, develop, and implement automation solutions for manufacturing processes.
Program, troubleshoot, and optimize PLCs, HMIs, SCADA systems, robotics, and industrial control systems.
Support the installation, commissioning, and validation of new production equipment.
Analyze manufacturing processes and identify opportunities to improve productivity, quality, safety, and cost.
Perform root cause analysis of equipment failures and implement corrective actions.
Develop and maintain electrical schematics, control system documentation, and standard operating procedures.
Collaborate with production, maintenance, quality, and engineering teams to resolve technical issues.
Lead or support capital automation projects from concept through implementation.
Ensure compliance with safety regulations, industry standards, and company policies.
Monitor equipment performance using data analysis and recommend continuous improvement initiatives.
Train production and maintenance personnel on new automation systems and equipment.
Maintain spare parts inventories and support preventive and predictive maintenance programs.
Required Qualifications
Bachelor's degree in Electrical Engineering, Mechanical Engineering, Mechatronics Engineering, Automation Engineering, or a related technical field.
3+ years of experience in manufacturing automation, industrial controls, or process engineering.
Experience programming PLCs (Allen-Bradley, Siemens, Mitsubishi, Omron, or similar).
Knowledge of industrial communication protocols such as Ethernet/IP, Modbus, Profinet, or DeviceNet.
Experience with robotics integration and automated material handling systems.
Strong understanding of electrical controls, sensors, actuators, servo systems, and VFDs.
Ability to read and interpret electrical schematics, P&IDs, and mechanical drawings.
Strong troubleshooting, analytical, and problem-solving skills.
Excellent communication and project management abilities.
Preferred Qualifications
Experience with Industry 4.0 technologies, IIoT, and data analytics.
Knowledge of vision inspection systems and machine safety standards.
Experience with SQL databases, Python, C#, or other programming languages.
Familiarity with Lean Manufacturing, Six Sigma, and continuous improvement methodologies.
Professional certifications in automation or controls engineering are a plus.
Key Competencies
Technical problem-solving
Project management
Process optimization
Continuous improvement mindset
Cross-functional collaboration
Attention to detail
Time management
Safety-first approach
Working Conditions
Manufacturing plant environment with exposure to industrial machinery.
Travel to contract manufacturing sites and suppliers
May require off-shift or weekend support during equipment installations or production emergencies.
Performance Metrics
Success in this role will be measured by:
Improvement in overall equipment effectiveness (OEE)
Increased production efficiency
Successful implementation of automation projects
Reduction in manufacturing defects
Compliance with safety and quality standards
Achievement of project timelines and budgets
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nJob Summary\n\nWe are seeking a skilled and motivated Manufacturing Automation Engineer to design, implement, maintain, and optimize automated manufacturing assembly and test systems. The ideal candidate will collaborate with cross-functional teams to improve production efficiency, enhance product quality, reduce downtime, and support continuous improvement initiatives through advanced automation technologies.\n\nKey Responsibilities\n\n - Design, develop, and implement automation solutions for manufacturing processes.\n\n - Program, troubleshoot, and optimize PLCs, HMIs, SCADA systems, robotics, and industrial control systems.\n\n - Support the installation, commissioning, and validation of new production equipment.\n\n - Analyze manufacturing processes and identify opportunities to improve productivity, quality, safety, and cost.\n\n - Perform root cause analysis of equipment failures and implement corrective actions.\n\n - Develop and maintain electrical schematics, control system documentation, and standard operating procedures.\n\n - Collaborate with production, maintenance, quality, and engineering teams to resolve technical issues.\n\n - Lead or support capital automation projects from concept through implementation.\n\n - Ensure compliance with safety regulations, industry standards, and company policies.\n\n - Monitor equipment performance using data analysis and recommend continuous improvement initiatives.\n\n - Train production and maintenance personnel on new automation systems and equipment.\n\n - Maintain spare parts inventories and support preventive and predictive maintenance programs.\n\nRequired Qualifications\n\n - Bachelor's degree in Electrical Engineering, Mechanical Engineering, Mechatronics Engineering, Automation Engineering, or a related technical field.\n\n - 3+ years of experience in manufacturing automation, industrial controls, or process engineering.\n\n - Experience programming PLCs (Allen-Bradley, Siemens, Mitsubishi, Omron, or similar).\n\n - Knowledge of industrial communication protocols such as Ethernet/IP, Modbus, Profinet, or DeviceNet.\n\n - Experience with robotics integration and automated material handling systems.\n\n - Strong understanding of electrical controls, sensors, actuators, servo systems, and VFDs.\n\n - Ability to read and interpret electrical schematics, P&IDs, and mechanical drawings.\n\n - Strong troubleshooting, analytical, and problem-solving skills.\n\n - Excellent communication and project management abilities.\n\nPreferred Qualifications\n\n - Experience with Industry 4.0 technologies, IIoT, and data analytics.\n\n - Knowledge of vision inspection systems and machine safety standards.\n\n - Experience with SQL databases, Python, C#, or other programming languages.\n\n - Familiarity with Lean Manufacturing, Six Sigma, and continuous improvement methodologies.\n\n - Professional certifications in automation or controls engineering are a plus.\n\nKey Competencies\n\n - Technical problem-solving\n\n - Project management\n\n - Process optimization\n\n - Continuous improvement mindset\n\n - Cross-functional collaboration\n\n - Attention to detail\n\n - Time management\n\n - Safety-first approach\n\nWorking Conditions\n\n - Manufacturing plant environment with exposure to industrial machinery.\n\n - Travel to contract manufacturing sites and suppliers\n\n - May require off-shift or weekend support during equipment installations or production emergencies.\n\nPerformance Metrics\n\nSuccess in this role will be measured by:\n\n - Improvement in overall equipment effectiveness (OEE)\n\n - Increased production efficiency\n\n - Successful implementation of automation projects\n\n - Reduction in manufacturing defects\n\n - Compliance with safety and quality standards\n\n - Achievement of project timelines and budgets\n\n\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"1bf0ea92-b0fd-4163-b44c-3564e67b15c1","title":"Principal SRE - AI Inference","department":"Software Engineering ","team":"Inference Service","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2026-07-06T20:38:40.281+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressRegion":"California ","addressCountry":"United States","addressLocality":"Sunnyvale "}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/1bf0ea92-b0fd-4163-b44c-3564e67b15c1","applyUrl":"https://jobs.ashbyhq.com/cerebras/1bf0ea92-b0fd-4163-b44c-3564e67b15c1/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About the Role
We are building a high-performance SRE function to support one of the world’s fastest-growing AI inference services, powered by the Wafer-Scale Engine (WSE). This team will help deliver world-class, ultra-reliable inference infrastructure for leading model builders such as OpenAI and other frontier labs.
As a Principal SRE, you will define and drive the technical architecture for scaling our inference fleet through self-service delivery, shared observability, capacity orchestration, rollout safety, and operational automation. This role starts with 2–3 weeks of hands-on operational immersion to build deep context on the current stack, production pain points, and high-stakes workflows.
From there, your mandate shifts to architecting the “tomorrow” layer: a unified capacity management and production control plane that enables reliable capacity planning, workload placement, rollout safety, validation, and operational decision-making across large-scale inference infrastructure.
Success in the first year means core engineering teams, product managers, external customers, and cluster stakeholders can execute critical operational workflows through self-service systems with strong guardrails, clear ownership, and minimal dependency on expert SRE operators.
You will collaborate with the tech leads and the leadership team across core, cluster, cloud, and product stakeholders. This work will shift reliability from an ops-only burden to a shared engineering discipline that underpins frontier AI inference at scale.
If you are a proven Principal engineer who enjoys turning complexity into elegant reliability at scale, this is your chance to lead this transformation from the front.
This role does not require 24/7 on-call rotations.
Key Responsibilities
Define and implement a robust strategy for delivering and running software reliably and at scale across multiple datacenters and cloud-based solutions.
Architect self-service platforms and internal tooling that let product teams, external customers, and cluster operators safely trigger and observe critical workflows with minimal handoffs.
Define and evolve reliability practices for inference workloads, including SLOs and SLIs for latency, throughput, and accuracy stability; error budgets; blameless postmortems; chaos testing; and capacity forecasting across multi-datacenter and on-prem environments.
Mentor senior SREs, support critical incident escalations, and use production pain points to prioritize the highest-leverage automation work.
Measure and drive impact through clear metrics, including toil reduction, deployment velocity, SLO compliance, MTTR, and adoption of self-service workflows.
Required Experience & Skills
15+ years in SRE, infrastructure engineering, or platform engineering, with a record of setting technical direction and delivering reliability improvements at large scale in FAANG, hyperscaler, frontier AI, or similarly demanding production environments.
Deep experience with large-scale compute fleets, internal control planes, schedulers, orchestration systems, capacity management, and reliability automation.
Experience defining and driving cross-team architecture for production control planes, capacity orchestration, fleet management, or self-service infrastructure platforms with clear operational ownership.
Strong judgment in converging fragmented workflows, tools, and teams into coherent architectures that improve reliability, efficiency, and operational leverage.
Ability to lead complex, ambiguous technical programs end to end; influence senior cross-functional stakeholders; mentor senior engineers; and communicate technical strategy clearly.
Hands-on experience with production observability, incident response, and SLO-based reliability management across metrics, logs, traces, alerting, dashboards, and operational review loops.
Nice-to-Haves
Experience with Bazel or other large-scale build systems in production.
Background in AI/ML inference systems, including model serving runtimes, disaggregated inference, GPU orchestration, latency and accuracy SLOs, or drift monitoring.
Prior work on predictive autoscaling, chaos engineering, or cost-aware capacity management for compute-intensive workloads.
Location
SF Bay Area
Toronto
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout the Role\n\nWe are building a high-performance SRE function to support one of the world’s fastest-growing AI inference services, powered by the Wafer-Scale Engine (WSE). This team will help deliver world-class, ultra-reliable inference infrastructure for leading model builders such as OpenAI and other frontier labs.\n\nAs a Principal SRE, you will define and drive the technical architecture for scaling our inference fleet through self-service delivery, shared observability, capacity orchestration, rollout safety, and operational automation. This role starts with 2–3 weeks of hands-on operational immersion to build deep context on the current stack, production pain points, and high-stakes workflows.\n\nFrom there, your mandate shifts to architecting the “tomorrow” layer: a unified capacity management and production control plane that enables reliable capacity planning, workload placement, rollout safety, validation, and operational decision-making across large-scale inference infrastructure.\n\nSuccess in the first year means core engineering teams, product managers, external customers, and cluster stakeholders can execute critical operational workflows through self-service systems with strong guardrails, clear ownership, and minimal dependency on expert SRE operators.\n\nYou will collaborate with the tech leads and the leadership team across core, cluster, cloud, and product stakeholders. This work will shift reliability from an ops-only burden to a shared engineering discipline that underpins frontier AI inference at scale.\n\nIf you are a proven Principal engineer who enjoys turning complexity into elegant reliability at scale, this is your chance to lead this transformation from the front.\n\nThis role does not require 24/7 on-call rotations.\n\nKey Responsibilities\n\n - Define and implement a robust strategy for delivering and running software reliably and at scale across multiple datacenters and cloud-based solutions.\n\n - Architect self-service platforms and internal tooling that let product teams, external customers, and cluster operators safely trigger and observe critical workflows with minimal handoffs.\n\n - Define and evolve reliability practices for inference workloads, including SLOs and SLIs for latency, throughput, and accuracy stability; error budgets; blameless postmortems; chaos testing; and capacity forecasting across multi-datacenter and on-prem environments.\n\n - Mentor senior SREs, support critical incident escalations, and use production pain points to prioritize the highest-leverage automation work.\n\n - Measure and drive impact through clear metrics, including toil reduction, deployment velocity, SLO compliance, MTTR, and adoption of self-service workflows.\n\nRequired Experience & Skills\n\n - 15+ years in SRE, infrastructure engineering, or platform engineering, with a record of setting technical direction and delivering reliability improvements at large scale in FAANG, hyperscaler, frontier AI, or similarly demanding production environments.\n\n - Deep experience with large-scale compute fleets, internal control planes, schedulers, orchestration systems, capacity management, and reliability automation.\n\n - Experience defining and driving cross-team architecture for production control planes, capacity orchestration, fleet management, or self-service infrastructure platforms with clear operational ownership.\n\n - Strong judgment in converging fragmented workflows, tools, and teams into coherent architectures that improve reliability, efficiency, and operational leverage.\n\n - Ability to lead complex, ambiguous technical programs end to end; influence senior cross-functional stakeholders; mentor senior engineers; and communicate technical strategy clearly.\n\n - Hands-on experience with production observability, incident response, and SLO-based reliability management across metrics, logs, traces, alerting, dashboards, and operational review loops.\n\nNice-to-Haves\n\n - Experience with Bazel or other large-scale build systems in production.\n\n - Background in AI/ML inference systems, including model serving runtimes, disaggregated inference, GPU orchestration, latency and accuracy SLOs, or drift monitoring.\n\n - Prior work on predictive autoscaling, chaos engineering, or cost-aware capacity management for compute-intensive workloads.\n\nLocation\n\n - SF Bay Area\n\n - Toronto\n\n\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"2b22599f-b1ee-46ef-8684-1475bc49bac0","title":"Cloud Infrastructure Engineer","department":"Software Engineering ","team":"Developer Productivity","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[{"location":"Toronto, CAN","address":{"postalAddress":{"postalCode":"M5H1Z5","addressRegion":"Ontario","streetAddress":"67 Richmond St W","addressCountry":"Canada","addressLocality":"Toronto"}}}],"publishedAt":"2026-08-25T19:33:09.604+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressRegion":"California ","addressCountry":"United States","addressLocality":"Sunnyvale "}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/2b22599f-b1ee-46ef-8684-1475bc49bac0","applyUrl":"https://jobs.ashbyhq.com/cerebras/2b22599f-b1ee-46ef-8684-1475bc49bac0/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Responsibilities:
Design, build, and operate secure, scalable cloud infrastructure and identity platforms in AWS and our own data centers.
Implement and manage IAM, IGA, authentication, authorization, SSO, MFA, identity lifecycle management, and provisioning/deprovisioning solutions using modern identity platforms and standards such as SAML, OAuth2, OIDC, and SCIM.
Develop automation, integrations, and infrastructure-as-code solutions using Terraform and programming languages such as Python and Go.
Design and implement security controls for AI-powered systems, including controlled, audited, and governed agent workflows, while contributing to core security services such as service identity, secrets management, key management, authentication, and authorization.
Partner with Security and Engineering teams to deliver secure-by-design solutions, implement Zero Trust principles, and reduce operational friction.
Write high-quality, reliable code, participate in architecture and code reviews, support critical production systems, and drive operational excellence through scalability, resiliency, and automation.
Be part of oncall and incident response of Dev Productivity org.
Skills & Qualifications
5+ years of experience in Cloud Infrastructure, Identity & Access Management (IAM), Identity Engineering, or Security Engineering.
Strong knowledge of authentication, authorization, identity lifecycle management, and federation protocols including SAML, OAuth2, OIDC, SCIM, and RBAC.
Experience designing and operating identity and access controls within AWS environments, with experience building and operating production level services on AWS.
Experience working with container technology.
Experience deploying and operating services on Kubernetes.
Strong automation and coding skills with Python, Go, Terraform, or similar technologies.
A security-first mindset with experience implementing Zero Trust, least-privilege access, and compliance frameworks such as SOC2, FedRAMP, or ITAR.
An product and operational mindset with experience supporting and improving production level services through monitoring, troubleshooting, incident response, and automation.
Excellent collaboration and communication skills, with a proven ability to drive projects and influence technical decisions across teams.
Preferred Skills & Qualifications
Hands-on experience with any Identity platforms - Okta, Microsoft Entra ID (Azure AD), and modern IAM/IGA platforms.
Experiences with Azure and/or GCP is a bonus.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nResponsibilities:\n\n - Design, build, and operate secure, scalable cloud infrastructure and identity platforms in AWS and our own data centers.\n\n - Implement and manage IAM, IGA, authentication, authorization, SSO, MFA, identity lifecycle management, and provisioning/deprovisioning solutions using modern identity platforms and standards such as SAML, OAuth2, OIDC, and SCIM.\n\n - Develop automation, integrations, and infrastructure-as-code solutions using Terraform and programming languages such as Python and Go.\n\n - Design and implement security controls for AI-powered systems, including controlled, audited, and governed agent workflows, while contributing to core security services such as service identity, secrets management, key management, authentication, and authorization.\n\n - Partner with Security and Engineering teams to deliver secure-by-design solutions, implement Zero Trust principles, and reduce operational friction.\n\n - Write high-quality, reliable code, participate in architecture and code reviews, support critical production systems, and drive operational excellence through scalability, resiliency, and automation.\n\n - Be part of oncall and incident response of Dev Productivity org.\n\n \nSkills & Qualifications\n\n - 5+ years of experience in Cloud Infrastructure, Identity & Access Management (IAM), Identity Engineering, or Security Engineering.\n\n - Strong knowledge of authentication, authorization, identity lifecycle management, and federation protocols including SAML, OAuth2, OIDC, SCIM, and RBAC.\n\n - Experience designing and operating identity and access controls within AWS environments, with experience building and operating production level services on AWS.\n\n - Experience working with container technology.\n\n - Experience deploying and operating services on Kubernetes.\n\n - Strong automation and coding skills with Python, Go, Terraform, or similar technologies.\n\n - A security-first mindset with experience implementing Zero Trust, least-privilege access, and compliance frameworks such as SOC2, FedRAMP, or ITAR.\n\n - An product and operational mindset with experience supporting and improving production level services through monitoring, troubleshooting, incident response, and automation.\n\n - Excellent collaboration and communication skills, with a proven ability to drive projects and influence technical decisions across teams.\n\n\nPreferred Skills & Qualifications\n\n - Hands-on experience with any Identity platforms - Okta, Microsoft Entra ID (Azure AD), and modern IAM/IGA platforms.\n\n - Experiences with Azure and/or GCP is a bonus.\n\n \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"c8fbf33e-a200-483f-8980-673a0a7dab53","title":"Mechanical Engineer - Datacenter Deliver","department":"Datacenters","team":"Datacenters","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2026-07-10T22:42:54.861+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressRegion":"California ","addressCountry":"United States","addressLocality":"Sunnyvale "}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/c8fbf33e-a200-483f-8980-673a0a7dab53","applyUrl":"https://jobs.ashbyhq.com/cerebras/c8fbf33e-a200-483f-8980-673a0a7dab53/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
The Role
We are seeking an experienced Mechanical Engineer to join the Data Center Delivery organization. This role will be responsible for technical oversight of mechanical infrastructure across leased AI data center deployments, ensuring facilities are designed, constructed, commissioned, and handed over to meet Cerebras' performance, reliability, scalability, and schedule requirements.
The Mechanical Engineer will serve as the owner's technical representative, partnering closely with colocation providers, developers, EPC contractors, OEMs, and internal infrastructure teams to deliver world-class AI computing facilities.
Unlike traditional data center development roles, this position focuses on technical governance, design reviews, owner acceptance, fit-out integration, and operational readiness rather than performing detailed engineering design.
Responsibilities
Serve as the subject matter expert for mechanical infrastructure across assigned projects.
Review and approve basis of design, drawings, equipment submittals, RFIs, and change requests.
Ensure compliance with Cerebras engineering standards.
Validate cooling architectures supporting high-density AI deployments.
White Space Delivery
Provide technical oversight for in-row/rear-door cooling systems
Coolant Distribution Units (CDUs)
Thermal expansion tanks
Buffer tanks
Stainless steel piping
Hot aisle containment
Mechanical supports
Leak detection systems
CRAH/CRAC integration
Water treatment systems
White space mechanical distribution
Colocation & Developer Management
Act as owner's representative during design, construction, and commissioning.
Review developer design decisions.
Participate in design workshops.
Resolve technical issues.
Evaluate value engineering proposals.
Ensure contracted mechanical scope is delivered.
Construction Support
Perform regular site inspections.
Monitor installation quality.
Review contractor installation methods.
Support schedule recovery planning.
Validate installations against approved drawings.
Participate in turnover inspections.
Commissioning
Support FAT, SAT, IST, FPT, mechanical startup, cooling optimization, and owner acceptance.
Review commissioning documentation and verify system performance prior to turnover.
Operational Readiness
Ensure complete O&M documentation.
Develop spare parts strategy.
Support maintenance procedures.
Verify asset documentation.
Coordinate training packages.
Manage mechanical warranties.
Cross Functional Collaboration
Work with Electrical Engineering, Network Engineering, Construction TPMs, Commissioning Managers, Capacity Planning, Operations, Procurement, colocation providers, and OEMs.
Skills & Qualifications
Required
Bachelor's degree in Mechanical Engineering.
8+ years in mission-critical facilities or hyperscale data centers.
Strong understanding of chilled water cooling systems.
Experience with high-density AI/HPC cooling.
Knowledge of data center cooling infrastructure.
Construction and commissioning experience.
Ability to interpret mechanical drawings.
Excellent communication and project management skills.
Preferred
PE license preferred.
Experience supporting leased data centers, hyperscale or AI data centers
Familiarity with liquid cooling.
Knowledge of ASHRAE thermal guidelines.
Experience with BIM/Revit/Navisworks.
Familiarity with CFD analysis.
Technical Expertise
Chilled water systems
Cooling towers
Heat exchangers
CDUs
Pumping systems
Buffer tanks
Expansion tanks
Stainless steel piping
Glycol systems
Water treatment
Hot aisle containment
High-density cooling
Leak detection
BMS integration
Mechanical commissioning
Root cause analysis
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nThe Role\n\nWe are seeking an experienced Mechanical Engineer to join the Data Center Delivery organization. This role will be responsible for technical oversight of mechanical infrastructure across leased AI data center deployments, ensuring facilities are designed, constructed, commissioned, and handed over to meet Cerebras' performance, reliability, scalability, and schedule requirements.\n\nThe Mechanical Engineer will serve as the owner's technical representative, partnering closely with colocation providers, developers, EPC contractors, OEMs, and internal infrastructure teams to deliver world-class AI computing facilities.\n\nUnlike traditional data center development roles, this position focuses on technical governance, design reviews, owner acceptance, fit-out integration, and operational readiness rather than performing detailed engineering design.\n\nResponsibilities\n\n - Serve as the subject matter expert for mechanical infrastructure across assigned projects.\n\n - Review and approve basis of design, drawings, equipment submittals, RFIs, and change requests.\n\n - Ensure compliance with Cerebras engineering standards.\n\n - Validate cooling architectures supporting high-density AI deployments.\n\nWhite Space Delivery\n\n - Provide technical oversight for in-row/rear-door cooling systems\n\n - Coolant Distribution Units (CDUs)\n\n - Thermal expansion tanks\n\n - Buffer tanks\n\n - Stainless steel piping\n\n - Hot aisle containment\n\n - Mechanical supports\n\n - Leak detection systems\n\n - CRAH/CRAC integration\n\n - Water treatment systems\n\n - White space mechanical distribution\n\nColocation & Developer Management\n\n - Act as owner's representative during design, construction, and commissioning.\n\n - Review developer design decisions.\n\n - Participate in design workshops.\n\n - Resolve technical issues.\n\n - Evaluate value engineering proposals.\n\n - Ensure contracted mechanical scope is delivered.\n\nConstruction Support\n\n - Perform regular site inspections.\n\n - Monitor installation quality.\n\n - Review contractor installation methods.\n\n - Support schedule recovery planning.\n\n - Validate installations against approved drawings.\n\n - Participate in turnover inspections.\n\nCommissioning\n\n - Support FAT, SAT, IST, FPT, mechanical startup, cooling optimization, and owner acceptance.\n\n - Review commissioning documentation and verify system performance prior to turnover.\n\nOperational Readiness\n\n - Ensure complete O&M documentation.\n\n - Develop spare parts strategy.\n\n - Support maintenance procedures.\n\n - Verify asset documentation.\n\n - Coordinate training packages.\n\n - Manage mechanical warranties.\n\nCross Functional Collaboration\n\n - Work with Electrical Engineering, Network Engineering, Construction TPMs, Commissioning Managers, Capacity Planning, Operations, Procurement, colocation providers, and OEMs.\n\n\n\nSkills & Qualifications\n\nRequired\n\n - Bachelor's degree in Mechanical Engineering.\n\n - 8+ years in mission-critical facilities or hyperscale data centers.\n\n - Strong understanding of chilled water cooling systems.\n\n - Experience with high-density AI/HPC cooling.\n\n - Knowledge of data center cooling infrastructure.\n\n - Construction and commissioning experience.\n\n - Ability to interpret mechanical drawings.\n\n - Excellent communication and project management skills.\n\nPreferred\n\n - PE license preferred.\n\n - Experience supporting leased data centers, hyperscale or AI data centers\n\n - Familiarity with liquid cooling.\n\n - Knowledge of ASHRAE thermal guidelines.\n\n - Experience with BIM/Revit/Navisworks.\n\n - Familiarity with CFD analysis.\n\nTechnical Expertise\n\n - Chilled water systems\n\n - Cooling towers\n\n - Heat exchangers\n\n - CDUs\n\n - Pumping systems\n\n - Buffer tanks\n\n - Expansion tanks\n\n - Stainless steel piping\n\n - Glycol systems\n\n - Water treatment\n\n - Hot aisle containment\n\n - High-density cooling\n\n - Leak detection\n\n - BMS integration\n\n - Mechanical commissioning\n\n - Root cause analysis\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"e825320a-b21f-40b0-9318-e71548f27640","title":"Senior SDET, Inference Platform ","department":"Software Engineering ","team":"Inference Service","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[{"location":"Sunnyvale, CA","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}}},{"location":"Toronto, CAN","address":{"postalAddress":{"addressRegion":"Ontario ","addressCountry":"Canada","addressLocality":"Toronto "}}}],"publishedAt":"2026-07-13T18:51:21.315+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressRegion":"California ","addressCountry":"United States","addressLocality":"Sunnyvale "}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/e825320a-b21f-40b0-9318-e71548f27640","applyUrl":"https://jobs.ashbyhq.com/cerebras/e825320a-b21f-40b0-9318-e71548f27640/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About the Role
We are looking for an Inference Platform SDET to join the Inference Service Quality team at Cerebras and work on the inference platform. This team sits at the intersection of distributed systems, cloud and cluster infrastructure, and the software stack that serves the world's fastest AI inference.
In this role, you will own the quality and reliability of the infrastructure that deploys and runs the Cerebras Inference Platform — from CI/CD pipelines and Kubernetes-based deployments to ingress, load balancing, and service discovery. You will validate the platform both in cloud environments and on real Cerebras clusters, working side by side with the Inference Platform development team to catch issues before our customers do.
This is an excellent opportunity for engineers who enjoy infrastructure, automation, and debugging across the full deployment stack, and who want to ensure that a platform serving inference at massive scale stays fast, reliable, and production-ready.
Responsibilities
Design, build, and maintain test infrastructure and automation for deploying and validating the Cerebras Inference Platform.
Validate the platform across environments — from cloud-managed Kubernetes to deployments running on Cerebras hardware.
Test and verify deployment infrastructure including Kubernetes workloads, CI/CD pipelines, ingress and service discovery, NGINX, and load balancing.
Collaborate closely with the Inference Platform development team to ensure new features and platform capabilities ship reliably.
Investigate and debug complex issues spanning networking, orchestration, deployment, and distributed services.
Develop and maintain testbeds used to validate platform performance, scalability, and reliability.
Identify failure points, bottlenecks, and edge cases that impact platform stability and inference performance.
Contribute to test plans and validation strategies for new platform features and releases.
Improve observability, diagnostics, and debugging workflows across the inference platform stack.
Partner with engineering teams to ensure high-quality, production-ready releases of the Cerebras Inference Platform.
Minimum Skills & Qualifications
3+ years of experience in software engineering, QA/quality engineering, systems engineering, or infrastructure development.
Strong programming skills in Python and/or Go (experience with both is a plus).
Experience building automation tools, testing frameworks, or internal developer tooling.
Hands-on experience with CI/CD systems (e.g., Jenkins)
Experience debugging complex systems, distributed services, or networked infrastructure.
Familiarity with systems-level development, infrastructure tooling, or platform integration.
Strong problem-solving skills and the ability to investigate issues across multiple system and infrastructure layers.
Excellent communication and collaboration skills.
Experience mentoring junior engineers
Preferred Skills
Hands-on experience with Kubernetes and container orchestration in a real production or staging environment.
Experience with cloud-managed Kubernetes such as Amazon EKS.
Experience with GitOps/deployment tooling (e.g., ArgoCD).
Familiarity with ingress controllers, service discovery, NGINX, and load balancing.
Experience with build systems such as Bazel.
Experience with cluster tooling and operations (e.g., k9s).
Exposure to performance debugging, profiling, or system observability tools.
Experience with ML inference infrastructure, model serving systems, or GPU-accelerated workloads
Location: Toronto / Sunnyvale
Team: Inference Service Quality
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout the Role\n\nWe are looking for an Inference Platform SDET to join the Inference Service Quality team at Cerebras and work on the inference platform. This team sits at the intersection of distributed systems, cloud and cluster infrastructure, and the software stack that serves the world's fastest AI inference.\n\n \n\nIn this role, you will own the quality and reliability of the infrastructure that deploys and runs the Cerebras Inference Platform — from CI/CD pipelines and Kubernetes-based deployments to ingress, load balancing, and service discovery. You will validate the platform both in cloud environments and on real Cerebras clusters, working side by side with the Inference Platform development team to catch issues before our customers do.\n\n \n\nThis is an excellent opportunity for engineers who enjoy infrastructure, automation, and debugging across the full deployment stack, and who want to ensure that a platform serving inference at massive scale stays fast, reliable, and production-ready.\n\n \n\nResponsibilities\n\n - Design, build, and maintain test infrastructure and automation for deploying and validating the Cerebras Inference Platform.\n\n - Validate the platform across environments — from cloud-managed Kubernetes to deployments running on Cerebras hardware.\n\n - Test and verify deployment infrastructure including Kubernetes workloads, CI/CD pipelines, ingress and service discovery, NGINX, and load balancing.\n\n - Collaborate closely with the Inference Platform development team to ensure new features and platform capabilities ship reliably.\n\n - Investigate and debug complex issues spanning networking, orchestration, deployment, and distributed services.\n\n - Develop and maintain testbeds used to validate platform performance, scalability, and reliability.\n\n - Identify failure points, bottlenecks, and edge cases that impact platform stability and inference performance.\n\n - Contribute to test plans and validation strategies for new platform features and releases.\n\n - Improve observability, diagnostics, and debugging workflows across the inference platform stack.\n\n - Partner with engineering teams to ensure high-quality, production-ready releases of the Cerebras Inference Platform.\n \n Minimum Skills & Qualifications\n\n - 3+ years of experience in software engineering, QA/quality engineering, systems engineering, or infrastructure development.\n\n - Strong programming skills in Python and/or Go (experience with both is a plus).\n\n - Experience building automation tools, testing frameworks, or internal developer tooling.\n\n - Hands-on experience with CI/CD systems (e.g., Jenkins)\n\n - Experience debugging complex systems, distributed services, or networked infrastructure.\n\n - Familiarity with systems-level development, infrastructure tooling, or platform integration.\n\n - Strong problem-solving skills and the ability to investigate issues across multiple system and infrastructure layers.\n\n - Excellent communication and collaboration skills.\n\n - Experience mentoring junior engineers\n\nPreferred Skills\n\n - Hands-on experience with Kubernetes and container orchestration in a real production or staging environment.\n\n - Experience with cloud-managed Kubernetes such as Amazon EKS.\n\n - Experience with GitOps/deployment tooling (e.g., ArgoCD).\n\n - Familiarity with ingress controllers, service discovery, NGINX, and load balancing.\n\n - Experience with build systems such as Bazel.\n\n - Experience with cluster tooling and operations (e.g., k9s).\n\n - Exposure to performance debugging, profiling, or system observability tools.\n\n - Experience with ML inference infrastructure, model serving systems, or GPU-accelerated workloads\n\nLocation: Toronto / Sunnyvale\n\nTeam: Inference Service Quality\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"c0d8fa46-fd9e-49b5-80c9-040bbd0da916","title":"Software Engineer - Tools & Infrastructure / DevOps","department":"Software Engineering ","team":"Developer Productivity","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[{"location":"Toronto, CAN","address":{"postalAddress":{"postalCode":"M5H1Z5","addressRegion":"Ontario","streetAddress":"67 Richmond St W","addressCountry":"Canada","addressLocality":"Toronto"}}}],"publishedAt":"2026-07-13T13:25:18.293+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressRegion":"California ","addressCountry":"United States","addressLocality":"Sunnyvale "}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/c0d8fa46-fd9e-49b5-80c9-040bbd0da916","applyUrl":"https://jobs.ashbyhq.com/cerebras/c0d8fa46-fd9e-49b5-80c9-040bbd0da916/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Responsibilities:
Contribute to the development and maintenance of CICD pipelines, ensuring reliable and efficient build, test, and release workflows across the organization.
Help manage artifact lifecycle systems including versioning, storage, distribution, and dependency management to support reproducible builds at scale.
Partner with development teams to design and improve code review workflows, branching strategies, and automated integration processes.
Provision, monitor, and optimize cloud infrastructure to support CI workloads, balancing cost efficiency with performance and reliability.
Troubleshoot build failures, pipeline bottlenecks, and infrastructure issues, driving root-cause analysis and implementing lasting fixes.
Contribute to internal build infrastructure, test infrastructure, tooling, and automation that improves developer velocity and engineering productivity.
Contribute to the company’s efforts on AI tooling to boost engineering productivity efficiently.
Skills & Qualifications
4-8 years of professional experience in a DevOps, infrastructure, or software engineering role.
Familiarity with CICD systems and hands-on experiences in building or maintaining automated build and deployment pipelines.
Understanding of artifact repository management and software packaging concepts.
Experience with cloud computing platforms (AWS preferred) and programmatic resource provisioning.
Proficiency with distributed version control systems, code review processes, and repository management.
Foundational knowledge of operating system concepts (Linux/Unix), networking fundamentals, and scripting for automation.
Experience with containerization and container orchestration (Kubernetes preferred).
Strong troubleshooting skills and a methodical approach to debugging distributed systems.
Curiosity about how large-scale infrastructure is built, operated, and improved.
Being part of oncall and incident response task force of Dev Productivity org.
Preferred Skills & Qualifications
Familiarity with infrastructure-as-code tools and practices.
Scripting proficiency in Python or Shell for build automation and tooling.
Exposure to build systems and build graph optimization.
Understanding of observability practices including monitoring, logging, and alerting.
BS/MS in Computer Science or a related field, or equivalent practical experience.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nResponsibilities:\n\n - Contribute to the development and maintenance of CICD pipelines, ensuring reliable and efficient build, test, and release workflows across the organization.\n\n - Help manage artifact lifecycle systems including versioning, storage, distribution, and dependency management to support reproducible builds at scale.\n\n - Partner with development teams to design and improve code review workflows, branching strategies, and automated integration processes.\n\n - Provision, monitor, and optimize cloud infrastructure to support CI workloads, balancing cost efficiency with performance and reliability.\n\n - Troubleshoot build failures, pipeline bottlenecks, and infrastructure issues, driving root-cause analysis and implementing lasting fixes.\n\n - Contribute to internal build infrastructure, test infrastructure, tooling, and automation that improves developer velocity and engineering productivity.\n\n - Contribute to the company’s efforts on AI tooling to boost engineering productivity efficiently.\n\n \n\nSkills & Qualifications\n\n - 4-8 years of professional experience in a DevOps, infrastructure, or software engineering role.\n\n - Familiarity with CICD systems and hands-on experiences in building or maintaining automated build and deployment pipelines.\n\n - Understanding of artifact repository management and software packaging concepts.\n\n - Experience with cloud computing platforms (AWS preferred) and programmatic resource provisioning.\n\n - Proficiency with distributed version control systems, code review processes, and repository management.\n\n - Foundational knowledge of operating system concepts (Linux/Unix), networking fundamentals, and scripting for automation.\n\n - Experience with containerization and container orchestration (Kubernetes preferred).\n\n - Strong troubleshooting skills and a methodical approach to debugging distributed systems.\n\n - Curiosity about how large-scale infrastructure is built, operated, and improved.\n\n - Being part of oncall and incident response task force of Dev Productivity org.\n\n\n\nPreferred Skills & Qualifications\n\n - Familiarity with infrastructure-as-code tools and practices.\n\n - Scripting proficiency in Python or Shell for build automation and tooling.\n\n - Exposure to build systems and build graph optimization.\n\n - Understanding of observability practices including monitoring, logging, and alerting.\n\n - BS/MS in Computer Science or a related field, or equivalent practical experience.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"708b4906-c873-40a1-9b6d-71b6fdda326e","title":"Senior Software Development Engineer in Test (SDET) - AI Cluster","department":"Software Engineering ","team":"Cluster","employmentType":"FullTime","location":"Toronto, CAN","secondaryLocations":[],"publishedAt":"2026-07-15T10:44:57.830+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"postalCode":"M5H1Z5","addressRegion":"Ontario","streetAddress":"67 Richmond St W","addressCountry":"Canada","addressLocality":"Toronto"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/708b4906-c873-40a1-9b6d-71b6fdda326e","applyUrl":"https://jobs.ashbyhq.com/cerebras/708b4906-c873-40a1-9b6d-71b6fdda326e/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
In AI infrastructure organization, simplifying large hardware deployments with push button, single pane of glass for observability/monitoring and software capabilities for build-in resiliency are some of the key focus areas. As senior software development engineer in Test, we are looking for a candidate who can make a big impact on how we test and validate thousands of nodes in large deployments to ensure the cluster is 99.999% reliable.
Responsibilities
You will be hired to innovate and execute tests on cutting edge AI infrastructure. Be a thinker, define optimized test strategies and methodologies.
Cerebras is growing and innovating at a rapid pace and so is the ML community and AI models. Be a quick learner, adapt to new technologies, and bring your expertise. We are looking to hire a team with a diverse skill set.
Deep understanding of how large-scale distributed ML training and inference works. Build a strong understanding of how to break these large distributed systems challenge into smaller components that can be unit tested.
Automate first approach - In large scale deployment, automation drives efficiency and scalability. Aim for 100% automated tests to test all cluster features in areas of high availability, failure scenarios, performance, stress and security.
Champion cluster security, reliability for uptime of 99.9999% and ease of use with observability.
Test all components of AI cluster including but not limited to cluster software involving kubernetes, prometheus and grafana. Cluster hardware components like ML wafer scale accelerators, CPU runtime nodes, High speed swarmx interconnect, High speed data transfer of weights through memoryx interconnect.
Qualifications
Bachelor's or master's degree in engineering in computer science, electrical, AI, data science or related field.
5+ years of experience in testing one of areas like enterprise software, distributed systems, datacenter hardware and software.
Strong coding skills in one of the programming languages like python, golang and C/C++.
Strong debugging skills to debug issues in large distributed systems, hardware, and software. Experience with debugging tools like pdb, gdb, strace and network monitors.
Strong understanding of operating systems internals like memory management, file system working, security and performance.
Strong understanding of datacenter layout, device performance characteristics like Servers, Memory, BIOS, PCIe, networking and storage.
Experience with cloud technologies like AWS, kubernetes and dockers. Monitoring tools like grafana, prometheus is huge plus.
Understanding and experience of ML model training and inference is a huge plus.
Understand of ML hardware accelerators like GPU, custom accelerator ASIC is a huge plus.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nIn AI infrastructure organization, simplifying large hardware deployments with push button, single pane of glass for observability/monitoring and software capabilities for build-in resiliency are some of the key focus areas. As senior software development engineer in Test, we are looking for a candidate who can make a big impact on how we test and validate thousands of nodes in large deployments to ensure the cluster is 99.999% reliable. \n \nResponsibilities\n \n\n - You will be hired to innovate and execute tests on cutting edge AI infrastructure. Be a thinker, define optimized test strategies and methodologies.\n\n - Cerebras is growing and innovating at a rapid pace and so is the ML community and AI models. Be a quick learner, adapt to new technologies, and bring your expertise. We are looking to hire a team with a diverse skill set.\n\n - Deep understanding of how large-scale distributed ML training and inference works. Build a strong understanding of how to break these large distributed systems challenge into smaller components that can be unit tested.\n\n - Automate first approach - In large scale deployment, automation drives efficiency and scalability. Aim for 100% automated tests to test all cluster features in areas of high availability, failure scenarios, performance, stress and security.\n\n - Champion cluster security, reliability for uptime of 99.9999% and ease of use with observability.\n\n - Test all components of AI cluster including but not limited to cluster software involving kubernetes, prometheus and grafana. Cluster hardware components like ML wafer scale accelerators, CPU runtime nodes, High speed swarmx interconnect, High speed data transfer of weights through memoryx interconnect.\n\n Qualifications\n\n \n\n - Bachelor's or master's degree in engineering in computer science, electrical, AI, data science or related field.\n\n - 5+ years of experience in testing one of areas like enterprise software, distributed systems, datacenter hardware and software.\n\n - Strong coding skills in one of the programming languages like python, golang and C/C++.\n\n - Strong debugging skills to debug issues in large distributed systems, hardware, and software. Experience with debugging tools like pdb, gdb, strace and network monitors.\n\n - Strong understanding of operating systems internals like memory management, file system working, security and performance.\n\n - Strong understanding of datacenter layout, device performance characteristics like Servers, Memory, BIOS, PCIe, networking and storage.\n\n - Experience with cloud technologies like AWS, kubernetes and dockers. Monitoring tools like grafana, prometheus is huge plus.\n\n - Understanding and experience of ML model training and inference is a huge plus.\n\n - Understand of ML hardware accelerators like GPU, custom accelerator ASIC is a huge plus.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"97c53713-0e4e-4cb8-b638-5add6bb1a987","title":"Senior ERP Systems Administrator","department":"IT & Security","team":"IT","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2026-07-14T16:04:14.712+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressRegion":"California ","addressCountry":"United States","addressLocality":"Sunnyvale "}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/97c53713-0e4e-4cb8-b638-5add6bb1a987","applyUrl":"https://jobs.ashbyhq.com/cerebras/97c53713-0e4e-4cb8-b638-5add6bb1a987/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Position Summary
Cerebras is seeking a highly skilled Senior ERP Systems Administrator to manage, support, and optimize enterprise business applications with primary responsibility for NetSuite and adjacent enterprise platforms. This role will serve as a key member of the Business Information Systems (BIS) team, supporting Finance, Supply Chain, Manufacturing, Procurement, and Corporate Operations.
The ideal candidate combines strong ERP administration expertise with business process knowledge and hands-on experience across enterprise platforms such as NetSuite, Oracle Cloud, SAP, Workday, Coupa, Salesforce, and related integrations.
This individual will own day-to-day production support, user administration, release management, configuration management, reporting, workflow administration, and operational governance while partnering closely with business stakeholders, developers, and solution architects.
Responsibilities
ERP Administration & Production Support
Administer and support NetSuite ERP and related enterprise applications.
Manage user provisioning, deprovisioning, role-based security, and access reviews.
Troubleshoot production issues and coordinate issue resolution.
Support month-end, quarter-end, and year-end business operations.
Monitor integrations, scheduled jobs, workflows, and system health.
Manage ticket queues and SLA adherence.
Coordinate release validation and production deployment support.
Document configurations, business processes, and support procedures.
Configuration & Optimization
Configure workflows, forms, saved searches, reports, dashboards, and security roles.
Perform minor enhancements and configuration changes.
Identify opportunities for automation and process improvements.
Support data integrity, master data governance, and operational controls.
Assist in evaluating new ERP functionality and platform capabilities.
Business Partnership
Partner with Finance, Accounting, Supply Chain, Procurement, Manufacturing, and IT teams.
Support User Acceptance Testing (UAT) activities.
Deliver end-user training and knowledge transfer.
Drive adoption of enterprise application best practices.
Governance & Compliance
Participate in SOX, audit, and compliance activities.
Support quarterly user access reviews and segregation-of-duties controls.
Ensure change management processes are followed.
Maintain system documentation and operational runbooks.
Cross-Platform Support
Support and collaborate across enterprise platforms including:
NetSuite ERP
Oracle Fusion Cloud
SAP S/4HANA
Workday
Coupa
Salesforce
NSPB / EPM platforms
Procurement and Supply Chain systems
Integration platforms (Celigo, Boomi, MuleSoft, Workato, etc.)
Required Qualifications
Experience
6+ years of ERP administration experience.
4+ years of hands-on NetSuite administration experience.
Experience supporting enterprise Finance and Supply Chain processes.
Experience administering at least one additional ERP platform:
Oracle Fusion Cloud
SAP S/4HANA
Workday Financials
Microsoft Dynamics
Experience supporting ERP integrations and third-party applications.
Experience working in SOX-controlled environments.
Business Process Knowledge
Strong understanding of:
Finance
General Ledger
Accounts Payable
Accounts Receivable
Revenue Recognition
Fixed Assets
Financial Reporting
Supply Chain
Procurement
Inventory Management
Manufacturing
Demand Planning
Order Management
Supplier Management
Preferred Qualifications
NetSuite Administrator Certification
Oracle Cloud Certification
SAP Certification
Workday Certification
ITIL Foundation Certification
Experience in high-growth technology companies
Experience supporting manufacturing organizations
Experience supporting AI, semiconductor, or hardware companies
Success Metrics (First 12 Months)
Achieve SLA compliance for production support.
Reduce ERP support backlog by 25%.
Improve ERP operational documentation coverage.
Complete quarterly access reviews with zero audit findings.
Improve ERP user satisfaction scores.
Successfully support major Finance and Supply Chain business cycles.
Deliver automation and process improvement initiatives
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nPosition Summary\n\nCerebras is seeking a highly skilled Senior ERP Systems Administrator to manage, support, and optimize enterprise business applications with primary responsibility for NetSuite and adjacent enterprise platforms. This role will serve as a key member of the Business Information Systems (BIS) team, supporting Finance, Supply Chain, Manufacturing, Procurement, and Corporate Operations.\n\n\n\nThe ideal candidate combines strong ERP administration expertise with business process knowledge and hands-on experience across enterprise platforms such as NetSuite, Oracle Cloud, SAP, Workday, Coupa, Salesforce, and related integrations.\n\n\n\nThis individual will own day-to-day production support, user administration, release management, configuration management, reporting, workflow administration, and operational governance while partnering closely with business stakeholders, developers, and solution architects.\n\n\n\nResponsibilities\n\n\n\nERP Administration & Production Support\n\n - Administer and support NetSuite ERP and related enterprise applications.\n\n - Manage user provisioning, deprovisioning, role-based security, and access reviews.\n\n - Troubleshoot production issues and coordinate issue resolution.\n\n - Support month-end, quarter-end, and year-end business operations.\n\n - Monitor integrations, scheduled jobs, workflows, and system health.\n\n - Manage ticket queues and SLA adherence.\n\n - Coordinate release validation and production deployment support.\n\n - Document configurations, business processes, and support procedures.\n\nConfiguration & Optimization\n\n - Configure workflows, forms, saved searches, reports, dashboards, and security roles.\n\n - Perform minor enhancements and configuration changes.\n\n - Identify opportunities for automation and process improvements.\n\n - Support data integrity, master data governance, and operational controls.\n\n - Assist in evaluating new ERP functionality and platform capabilities.\n\nBusiness Partnership\n\n - Partner with Finance, Accounting, Supply Chain, Procurement, Manufacturing, and IT teams.\n\n - Support User Acceptance Testing (UAT) activities.\n\n - Deliver end-user training and knowledge transfer.\n\n - Drive adoption of enterprise application best practices.\n\nGovernance & Compliance\n\n - Participate in SOX, audit, and compliance activities.\n\n - Support quarterly user access reviews and segregation-of-duties controls.\n\n - Ensure change management processes are followed.\n\n - Maintain system documentation and operational runbooks.\n\nCross-Platform Support\n\nSupport and collaborate across enterprise platforms including:\n\n - NetSuite ERP\n\n - Oracle Fusion Cloud\n\n - SAP S/4HANA\n\n - Workday\n\n - Coupa\n\n - Salesforce\n\n - NSPB / EPM platforms\n\n - Procurement and Supply Chain systems\n\n - Integration platforms (Celigo, Boomi, MuleSoft, Workato, etc.)\n\n\n\nRequired Qualifications\n\nExperience\n\n - 6+ years of ERP administration experience.\n\n - 4+ years of hands-on NetSuite administration experience.\n\n - Experience supporting enterprise Finance and Supply Chain processes.\n\n - Experience administering at least one additional ERP platform:\n\n - Oracle Fusion Cloud\n\n - SAP S/4HANA\n\n - Workday Financials\n\n - Microsoft Dynamics\n\n - Experience supporting ERP integrations and third-party applications.\n\n - Experience working in SOX-controlled environments.\n\n\n\nBusiness Process Knowledge\n\n\n\nStrong understanding of:\n\nFinance\n\n - General Ledger\n\n - Accounts Payable\n\n - Accounts Receivable\n\n - Revenue Recognition\n\n - Fixed Assets\n\n - Financial Reporting\n\nSupply Chain\n\n - Procurement\n\n - Inventory Management\n\n - Manufacturing\n\n - Demand Planning\n\n - Order Management\n\n - Supplier Management\n\nPreferred Qualifications\n\n - NetSuite Administrator Certification\n\n - Oracle Cloud Certification\n\n - SAP Certification\n\n - Workday Certification\n\n - ITIL Foundation Certification\n\n - Experience in high-growth technology companies\n\n - Experience supporting manufacturing organizations\n\n - Experience supporting AI, semiconductor, or hardware companies\n\n\n\nSuccess Metrics (First 12 Months)\n\n - Achieve SLA compliance for production support.\n\n - Reduce ERP support backlog by 25%.\n\n - Improve ERP operational documentation coverage.\n\n - Complete quarterly access reviews with zero audit findings.\n\n - Improve ERP user satisfaction scores.\n\n - Successfully support major Finance and Supply Chain business cycles.\n\n - Deliver automation and process improvement initiatives\n\n\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"e4bc1ea1-5401-4a3a-af22-21be3378aa4a","title":"Tech Lead Manager, Developer Productivity","department":"Software Engineering ","team":"Developer Productivity","employmentType":"FullTime","location":"Bengaluru, IND","secondaryLocations":[],"publishedAt":"2026-07-14T17:00:37.631+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressRegion":"Karnataka ","addressCountry":"India","addressLocality":"Bengaluru"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/e4bc1ea1-5401-4a3a-af22-21be3378aa4a","applyUrl":"https://jobs.ashbyhq.com/cerebras/e4bc1ea1-5401-4a3a-af22-21be3378aa4a/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Cerebras is looking for a Tech Lead Manager to lead our AI-Native Developer Productivity & Infrastructure team in Bengaluru.
This is not a traditional developer tools role. Cerebras is moving its software development organization to an AI-first model: engineers working with coding agents, AI-assisted debugging, automated failure analysis, intelligent CI, self-service environments, and infrastructure that is designed for both humans and agents. This role is an opportunity to help define that transformation from the ground up.
You will lead the team responsible for the systems that determine how fast Cerebras engineers can build, test, debug, integrate, and ship software. The scope includes CI/CD, merge queue and pre-qualification systems, build and test performance, developer observability, cloud and on-prem development environments, incident response, infrastructure automation, and AI-native workflows that reduce friction across the engineering organization.
The right candidate is both a technical leader and a builder of teams. You should be excited to manage and mentor engineers, set technical direction, stay close to architecture and execution, and work directly with senior engineering leaders to reimagine how a world-class AI hardware/software company builds software.
This is a fast-growing team and you will get a chance to own and define the strategy, vision, and plan for how to increase developer productivity.
Lead and grow a Bengaluru-based engineering team focused on AI-native developer productivity, infrastructure, and engineering acceleration.
Mentor engineers, review designs, guide architecture, and set a high bar for engineering quality, reliability, and operational excellence.
Own the delivery of key initiatives focused on improving developer experience and velocity across the engineering organization.
Build systems that improve developer turnaround time, including faster builds, lower queue latency, shorter test cycles, better flaky-test management, and clearer failure diagnosis.
Evaluate and adopt development tools and workflows, and guide the organization in effectively leveraging them to improve productivity and code quality.
Partner with engineering teams to ensure these tools are effectively integrated into day-to-day workflows and deliver measurable impact.
Lead war rooms and incident management for critical developer infrastructure issues, driving clear communication, rapid resolution, root-cause analysis, and durable follow-up actions.
Stay hands-on to understand the technical details, debug critical issues, and make strong architectural tradeoffs.
Are deeply focused on developer productivity and reducing friction across the software development lifecycle.
Have a proven track record of building tools and infrastructure that materially improve engineering velocity, reliability, and developer experience. You bring firsthand empathy for the tools, processes, and pain points that create toil, frustration, or burnout for engineering teams.
Have deep experience and strong technical judgment with build systems, CI/CD pipelines, and/or developer tooling in large monorepo environments.
Have strong programming ability in Python or similar systems-oriented languages.
Have engineering leadership experience as an engineering manager, tech lead, or tech lead manager, including experience hiring and growing teams.
Communicate clearly and influence effectively across globally distributed engineering teams.
Show high ownership, strong execution, and sound judgment in ambiguous environments where the right answer is not always obvious.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n\nABOUT THE ROLE\n\nCerebras is looking for a Tech Lead Manager to lead our AI-Native Developer Productivity & Infrastructure team in Bengaluru.\n\nThis is not a traditional developer tools role. Cerebras is moving its software development organization to an AI-first model: engineers working with coding agents, AI-assisted debugging, automated failure analysis, intelligent CI, self-service environments, and infrastructure that is designed for both humans and agents. This role is an opportunity to help define that transformation from the ground up.\n\nYou will lead the team responsible for the systems that determine how fast Cerebras engineers can build, test, debug, integrate, and ship software. The scope includes CI/CD, merge queue and pre-qualification systems, build and test performance, developer observability, cloud and on-prem development environments, incident response, infrastructure automation, and AI-native workflows that reduce friction across the engineering organization.\n\nThe right candidate is both a technical leader and a builder of teams. You should be excited to manage and mentor engineers, set technical direction, stay close to architecture and execution, and work directly with senior engineering leaders to reimagine how a world-class AI hardware/software company builds software.\n\nThis is a fast-growing team and you will get a chance to own and define the strategy, vision, and plan for how to increase developer productivity.\n\n\nRESPONSIBILITIES\n\n - Lead and grow a Bengaluru-based engineering team focused on AI-native developer productivity, infrastructure, and engineering acceleration.\n\n - Mentor engineers, review designs, guide architecture, and set a high bar for engineering quality, reliability, and operational excellence.\n\n - Own the delivery of key initiatives focused on improving developer experience and velocity across the engineering organization.\n\n - Build systems that improve developer turnaround time, including faster builds, lower queue latency, shorter test cycles, better flaky-test management, and clearer failure diagnosis.\n\n - Evaluate and adopt development tools and workflows, and guide the organization in effectively leveraging them to improve productivity and code quality.\n\n - Partner with engineering teams to ensure these tools are effectively integrated into day-to-day workflows and deliver measurable impact.\n\n - Lead war rooms and incident management for critical developer infrastructure issues, driving clear communication, rapid resolution, root-cause analysis, and durable follow-up actions.\n\n - Stay hands-on to understand the technical details, debug critical issues, and make strong architectural tradeoffs.\n\n\n REQUIREMENTS\n\n - Are deeply focused on developer productivity and reducing friction across the software development lifecycle.\n\n - Have a proven track record of building tools and infrastructure that materially improve engineering velocity, reliability, and developer experience. You bring firsthand empathy for the tools, processes, and pain points that create toil, frustration, or burnout for engineering teams.\n\n - Have deep experience and strong technical judgment with build systems, CI/CD pipelines, and/or developer tooling in large monorepo environments.\n\n - Have strong programming ability in Python or similar systems-oriented languages.\n\n - Have engineering leadership experience as an engineering manager, tech lead, or tech lead manager, including experience hiring and growing teams.\n\n - Communicate clearly and influence effectively across globally distributed engineering teams.\n\n - Show high ownership, strong execution, and sound judgment in ambiguous environments where the right answer is not always obvious.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"6c6a842b-0061-4424-ad90-12a926acb30f","title":"CoDesign & NextGen Performance Engineer","department":"Software Engineering ","team":"CoDesign","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[{"location":"Toronto, CAN","address":{"postalAddress":{"postalCode":"M5H1Z5","addressRegion":"Ontario","streetAddress":"67 Richmond St W","addressCountry":"Canada","addressLocality":"Toronto"}}}],"publishedAt":"2026-07-14T20:38:37.834+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressRegion":"California ","addressCountry":"United States","addressLocality":"Sunnyvale "}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/6c6a842b-0061-4424-ad90-12a926acb30f","applyUrl":"https://jobs.ashbyhq.com/cerebras/6c6a842b-0061-4424-ad90-12a926acb30f/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
This role focuses on characterizing, analyzing, and optimizing the performance of state-of-the-art AI models running on Cerebras’ breakthrough hardware. You will work across the hardware and software stack to identify bottlenecks, improve computational efficiency, and help influence the design of Cerebras’ next-generation AI architecture and software systems.
Responsibilities
Bring up and optimize performance on new generations of the Cerebras WSE.
Build performance models (kernel-level, end-to-end) to estimate the performance of state of the art and customer ML models.
Optimize and debug our kernel micro code and compiler algorithms to elevate ML model inference speed, throughput and compute utilization on the Cerebras WSE.
Debug and understand runtime performance on the system and cluster.
Develop tools and infrastructure to help visualize performance data collected from the Wafer Scale Engine and our compute cluster.
Skills & Qualifications
Bachelors / Masters / PhD in Electrical Engineering or Computer Science.
Strong background in computer architecture.
Exposure to and understanding of low-level deep learning / LLM math.
Strong analytical and problem-solving mindset.
3+ years of experience in a relevant domain (Computer Architecture, CPU/GPU Performance, Kernel Optimization, HPC).
Experience working on CPU/GPU simulators.
Exposure to performance profiling and debug on any system pipeline.
Comfort with C++ and Python.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nThis role focuses on characterizing, analyzing, and optimizing the performance of state-of-the-art AI models running on Cerebras’ breakthrough hardware. You will work across the hardware and software stack to identify bottlenecks, improve computational efficiency, and help influence the design of Cerebras’ next-generation AI architecture and software systems.\n\n\n\nResponsibilities\n\n - Bring up and optimize performance on new generations of the Cerebras WSE.\n\n - Build performance models (kernel-level, end-to-end) to estimate the performance of state of the art and customer ML models.\n\n - Optimize and debug our kernel micro code and compiler algorithms to elevate ML model inference speed, throughput and compute utilization on the Cerebras WSE.\n\n - Debug and understand runtime performance on the system and cluster.\n\n - Develop tools and infrastructure to help visualize performance data collected from the Wafer Scale Engine and our compute cluster.\n\n\n\nSkills & Qualifications\n\n - Bachelors / Masters / PhD in Electrical Engineering or Computer Science.\n Strong background in computer architecture.\n\n - Exposure to and understanding of low-level deep learning / LLM math.\n\n - Strong analytical and problem-solving mindset.\n\n - 3+ years of experience in a relevant domain (Computer Architecture, CPU/GPU Performance, Kernel Optimization, HPC).\n\n - Experience working on CPU/GPU simulators.\n\n - Exposure to performance profiling and debug on any system pipeline.\n\n - Comfort with C++ and Python.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"bf6f81b2-f079-483a-9238-295a184b3f0f","title":"Simulation Engineer","department":"Software Engineering ","team":"CoDesign","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[{"location":"Toronto, CAN","address":{"postalAddress":{"postalCode":"M5H1Z5","addressRegion":"Ontario","streetAddress":"67 Richmond St W","addressCountry":"Canada","addressLocality":"Toronto"}}}],"publishedAt":"2026-07-14T21:34:30.793+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressRegion":"California ","addressCountry":"United States","addressLocality":"Sunnyvale "}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/bf6f81b2-f079-483a-9238-295a184b3f0f","applyUrl":"https://jobs.ashbyhq.com/cerebras/bf6f81b2-f079-483a-9238-295a184b3f0f/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
As a Software Engineer on the Simulator Team (New College Grad), you will help build and improve the core simulation infrastructure for the next-generation Cerebras Wafer-Scale Engine (WSE). This role spans multiple simulator efforts, including functional simulation and pipeline-accurate simulation, based on team priorities and product needs.
The Simulator team builds foundational internal tools used across Cerebras for hardware and software co-development. These tools give kernel developers, compiler and runtime teams, architects, and design verification engineers visibility into both correctness and performance. Your work will help teams validate architectural behavior, understand performance tradeoffs, and move faster as new systems come online.
You will contribute to simulator architecture, model development, tooling, testing, and runtime optimization, working closely with cross-functional teams to keep our simulators accurate, scalable, and useful in day-to-day development.
Responsibilities
Develop and maintain simulator infrastructure in C++ for next-generation WSE systems.
Contribute to both functional simulation (architectural correctness, instruction behavior, and state and memory semantics) and pipeline-accurate simulation (execution behavior, bottleneck analysis, and performance visibility).
Build features and tooling that improve kernel developer visibility into correctness and performance.
Work with Design Verification and architecture teams to align simulator behavior with hardware specifications and validate design correctness.
Build and maintain strong unit, integration, and regression test coverage for simulator quality.
Improve simulator runtime performance, scalability, and usability for internal engineering workflows.
Debug complex issues that span simulator models, kernels, compiler/runtime interactions, and hardware assumptions.
Contribute to code reviews, documentation, and continuous improvement of engineering workflows.
Skills & Qualifications
Bachelor's or Master's degree (or equivalent) in Computer Science, Computer Engineering, or a related field.
Strong C++ programming skills and software engineering fundamentals.
Solid understanding of computer architecture concepts, including instruction execution, memory systems, and microarchitecture basics.
Strong debugging, analytical, and problem-solving skills.
Ability to collaborate effectively across software and hardware teams.
Preferred Skills & Qualifications
Familiarity with architectural, functional, or performance modeling.
Experience with test automation, regression systems, and CI pipelines.
Exposure to Python or scripting for tooling and automation.
Familiarity with parallel systems, accelerators, or ML/HPC workloads.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nAs a Software Engineer on the Simulator Team (New College Grad), you will help build and improve the core simulation infrastructure for the next-generation Cerebras Wafer-Scale Engine (WSE). This role spans multiple simulator efforts, including functional simulation and pipeline-accurate simulation, based on team priorities and product needs.\n\nThe Simulator team builds foundational internal tools used across Cerebras for hardware and software co-development. These tools give kernel developers, compiler and runtime teams, architects, and design verification engineers visibility into both correctness and performance. Your work will help teams validate architectural behavior, understand performance tradeoffs, and move faster as new systems come online.\n\nYou will contribute to simulator architecture, model development, tooling, testing, and runtime optimization, working closely with cross-functional teams to keep our simulators accurate, scalable, and useful in day-to-day development.\n\n\n\nResponsibilities\n\n - Develop and maintain simulator infrastructure in C++ for next-generation WSE systems.\n\n - Contribute to both functional simulation (architectural correctness, instruction behavior, and state and memory semantics) and pipeline-accurate simulation (execution behavior, bottleneck analysis, and performance visibility).\n\n - Build features and tooling that improve kernel developer visibility into correctness and performance.\n\n - Work with Design Verification and architecture teams to align simulator behavior with hardware specifications and validate design correctness.\n\n - Build and maintain strong unit, integration, and regression test coverage for simulator quality.\n\n - Improve simulator runtime performance, scalability, and usability for internal engineering workflows.\n\n - Debug complex issues that span simulator models, kernels, compiler/runtime interactions, and hardware assumptions.\n\n - Contribute to code reviews, documentation, and continuous improvement of engineering workflows.\n\n\n\nSkills & Qualifications\n\n - Bachelor's or Master's degree (or equivalent) in Computer Science, Computer Engineering, or a related field.\n\n - Strong C++ programming skills and software engineering fundamentals.\n\n - Solid understanding of computer architecture concepts, including instruction execution, memory systems, and microarchitecture basics.\n\n - Strong debugging, analytical, and problem-solving skills.\n\n - Ability to collaborate effectively across software and hardware teams.\n\n\n\nPreferred Skills & Qualifications\n\n - Familiarity with architectural, functional, or performance modeling.\n\n - Experience with test automation, regression systems, and CI pipelines.\n\n - Exposure to Python or scripting for tooling and automation.\n\n - Familiarity with parallel systems, accelerators, or ML/HPC workloads.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"ab6ab5f5-14b7-40d1-9070-e7b4517005b1","title":"Technical Business Development Manager","department":"Sales & Partnerships","team":"Partnerships","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2026-07-14T22:37:45.278+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California ","addressCountry":"United States","addressLocality":"Sunnyvale "}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/ab6ab5f5-14b7-40d1-9070-e7b4517005b1","applyUrl":"https://jobs.ashbyhq.com/cerebras/ab6ab5f5-14b7-40d1-9070-e7b4517005b1/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
We are seeking a highly motivated Deal Sourcing & Acquisition Analyst to support the Head of Data Center Acquisition in building and managing a high-quality pipeline of data center capacity opportunities. This role focuses on front-end sourcing, market intelligence, and deal triage to ensure a steady flow of credible, executable opportunities.
You will operate at the intersection of market research, outreach, and early-stage diligence, helping separate real capacity from speculative supply. This is a tactical, execution-driven role requiring strong organization and proactive engagement.
Source colocation, powered shell, land + power, and expansion opportunities
Conduct broker outreach, direct owner engagement, and cold outreach
Build and manage a global pipeline using CRM tools
Identify emerging clusters and supply-demand imbalances
Screen opportunities for power, permitting, and credibility
Produce structured deal summaries
Validate provider claims (power, schedule, capacity)
Organize diligence materials and flag risks early
Build network with developers, brokers, and operators
Track interactions and maintain ongoing engagement
Track deal stage, MW capacity, timeline, and risks
Support reporting and investment memos
Improve sourcing workflows and qualification frameworks
Support scalable sourcing engine development
1–4 years in acquisitions, real estate, infrastructure, or sourcing
Strong outreach and pipeline-building capability
Analytical and organizational skills
Exposure to data centers, power infrastructure, or telecom
Experience supporting diligence or underwriting
Market analysis experience
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n\n\n\nTHE ROLE\n\n\n\nWe are seeking a highly motivated Deal Sourcing & Acquisition Analyst to support the Head of Data Center Acquisition in building and managing a high-quality pipeline of data center capacity opportunities. This role focuses on front-end sourcing, market intelligence, and deal triage to ensure a steady flow of credible, executable opportunities. \n\n\n\nYou will operate at the intersection of market research, outreach, and early-stage diligence, helping separate real capacity from speculative supply. This is a tactical, execution-driven role requiring strong organization and proactive engagement.\n\n\n\n\nKEY RESPONSIBILITIES\n\n\n\n\nDEAL SOURCING & PIPELINE DEVELOPMENT\n\n - Source colocation, powered shell, land + power, and expansion opportunities\n\n - Conduct broker outreach, direct owner engagement, and cold outreach\n\n - Build and manage a global pipeline using CRM tools\n\n\nMARKET INTELLIGENCE & SCREENING\n\n - Identify emerging clusters and supply-demand imbalances\n\n - Screen opportunities for power, permitting, and credibility\n\n - Produce structured deal summaries\n\n\nEARLY-STAGE DILIGENCE SUPPORT\n\n - Validate provider claims (power, schedule, capacity)\n\n - Organize diligence materials and flag risks early\n\n\nRELATIONSHIP DEVELOPMENT\n\n - Build network with developers, brokers, and operators\n\n - Track interactions and maintain ongoing engagement\n\n\nDEAL TRACKING & COORDINATION\n\n - Track deal stage, MW capacity, timeline, and risks\n\n - Support reporting and investment memos\n\n\nPROCESS & TOOLING\n\n - Improve sourcing workflows and qualification frameworks\n\n - Support scalable sourcing engine development\n\n\n\n\nQUALIFICATIONS \n\n\n\n\nREQUIRED:\n\n - 1–4 years in acquisitions, real estate, infrastructure, or sourcing\n\n - Strong outreach and pipeline-building capability\n\n - Analytical and organizational skills\n\n\nPREFERRED:\n\n - Exposure to data centers, power infrastructure, or telecom\n\n - Experience supporting diligence or underwriting\n\n - Market analysis experience\n \n \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"07120606-8ddb-43bd-8e79-453573c84760","title":"Infrastructure Engineer (Data Center Operations)","department":"Software Engineering ","team":"Cluster","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2026-07-16T05:26:33.772+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressRegion":"California ","addressCountry":"United States","addressLocality":"Sunnyvale "}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/07120606-8ddb-43bd-8e79-453573c84760","applyUrl":"https://jobs.ashbyhq.com/cerebras/07120606-8ddb-43bd-8e79-453573c84760/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About the Role: We are looking for a hands-on Infrastructure Engineer to join our team and support our high-performance, on-premise server and networking infrastructure. You will be responsible for maintaining, provisioning, and troubleshooting hardware and Linux systems, working closely with network and system teams. This is an in-person role, ideal for someone who enjoys working across hardware, networking, and system layers.
Key Responsibilities:
Physically install, rack, cable, and maintain blade servers and hardware components (CPUs, DIMMs, NICs, storage devices, etc.)
Connect servers to high-speed networks (100G/400G), verify optics/DACs, and check link status
Configure BIOS, firmware, and out-of-band management (IPMI/iDRAC/iLO)
Install and provision Linux OS; configure hostnames, IPs, routing, and NFS mount points
Debug network issues at physical and OS level (VLAN, link issues, routing, etc.)
Use Linux tools (e.g., ip, dmesg, netstat, ping) to isolate and fix issues
Follow provisioning playbooks and maintain accurate records of assets and changes
Use scripting (Bash, Python) to automate routine tasks and improve efficiency
Collaborate with internal teams (network, systems, storage) and coordinate vendor RMAs
Document procedures and contribute to team knowledge base
Troubleshoot and replace failed server components with minimal downtime
Qualifications:
3–5+ years of experience in data center, lab, or infrastructure engineering roles
Proficient in Linux system administration and network configuration
Strong hands-on knowledge of x86 server hardware and enterprise networking
Familiar with BIOS configuration, firmware updates, and remote management tools
Skilled in physical setup and troubleshooting of high-speed NICs and optical links
Experience with VLANs, static routing, and diagnosing layer 1–3 issues
Ability to write scripts for automation and diagnostics (Bash, Python preferred)
Comfortable working on-site daily and lifting/moving server hardware
Preferred Skills:
Experience with PXE, NFS, RAID controllers, and monitoring tools
Familiarity with configuration management tools (e.g., Ansible)
Prior experience in a lab or R&D hardware/software environment
This is a unique opportunity to work with cutting-edge infrastructure and grow into more senior technical roles. If you enjoy bridging hardware and software with hands-on work, we’d love to hear from you.ADD DESCRIPTION HERE
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout the Role: We are looking for a hands-on Infrastructure Engineer to join our team and support our high-performance, on-premise server and networking infrastructure. You will be responsible for maintaining, provisioning, and troubleshooting hardware and Linux systems, working closely with network and system teams. This is an in-person role, ideal for someone who enjoys working across hardware, networking, and system layers.\n\n\n\nKey Responsibilities:\n\n - Physically install, rack, cable, and maintain blade servers and hardware components (CPUs, DIMMs, NICs, storage devices, etc.)\n\n - Connect servers to high-speed networks (100G/400G), verify optics/DACs, and check link status\n\n - Configure BIOS, firmware, and out-of-band management (IPMI/iDRAC/iLO)\n\n - Install and provision Linux OS; configure hostnames, IPs, routing, and NFS mount points\n\n - Debug network issues at physical and OS level (VLAN, link issues, routing, etc.)\n\n - Use Linux tools (e.g., ip, dmesg, netstat, ping) to isolate and fix issues\n\n - Follow provisioning playbooks and maintain accurate records of assets and changes\n\n - Use scripting (Bash, Python) to automate routine tasks and improve efficiency\n\n - Collaborate with internal teams (network, systems, storage) and coordinate vendor RMAs\n\n - Document procedures and contribute to team knowledge base\n\n - Troubleshoot and replace failed server components with minimal downtime\n\n\n\nQualifications:\n\n - 3–5+ years of experience in data center, lab, or infrastructure engineering roles\n\n - Proficient in Linux system administration and network configuration\n\n - Strong hands-on knowledge of x86 server hardware and enterprise networking\n\n - Familiar with BIOS configuration, firmware updates, and remote management tools\n\n - Skilled in physical setup and troubleshooting of high-speed NICs and optical links\n\n - Experience with VLANs, static routing, and diagnosing layer 1–3 issues\n\n - Ability to write scripts for automation and diagnostics (Bash, Python preferred)\n\n - Comfortable working on-site daily and lifting/moving server hardware\n\n\n\nPreferred Skills:\n\n - Experience with PXE, NFS, RAID controllers, and monitoring tools\n\n - Familiarity with configuration management tools (e.g., Ansible)\n\n - Prior experience in a lab or R&D hardware/software environment\n\n\n\nThis is a unique opportunity to work with cutting-edge infrastructure and grow into more senior technical roles. If you enjoy bridging hardware and software with hands-on work, we’d love to hear from you.ADD DESCRIPTION HERE\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"ba24de32-d882-4e27-b398-90e6356297c5","title":"Senior Software Development Engineer in Test (SDET) - AI Cluster Networking and Security ","department":"Software Engineering ","team":"Cluster","employmentType":"FullTime","location":"Bengaluru, IND","secondaryLocations":[],"publishedAt":"2026-07-16T05:36:32.323+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressRegion":"Karnataka ","addressCountry":"India","addressLocality":"Bengaluru"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/ba24de32-d882-4e27-b398-90e6356297c5","applyUrl":"https://jobs.ashbyhq.com/cerebras/ba24de32-d882-4e27-b398-90e6356297c5/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
In AI infrastructure organization, simplifying large hardware deployments with push button, single pane of glass for observability/monitoring and software capabilities for build-in resiliency are some of the key focus areas. As senior software development engineer in Test, we are looking for a candidate who can make a big impact on how we test and validate thousands of nodes in large deployments to ensure the cluster is 99.999% reliable.
Responsibities:
You will be hired to innovate and execute tests on cutting edge AI infrastructure. Be a thinker, define optimized test strategies and methodologies.
Cerebras is growing and innovating at a rapid pace and so is the ML community and AI models. Be a quick learner, adapt to new technologies, and bring your expertise. We are looking to hire a team with a diverse skill set.
Deep understanding of how large-scale distributed ML training and inference works. Build a strong understanding of how to break these large distributed systems challenge into smaller components that can be unit tested
Automate first approach - In large scale deployment, automation drives efficiency and scalability. Aim for 100% automated tests to test all cluster features in areas of high availability, failure scenarios, performance, stress and security
Champion cluster security, reliability for uptime of 99.9999% and ease of use with observability.
Test all components of AI cluster including but not limited to cluster software involving kubernetes, prometheus and grafana. Cluster hardware components like ML wafer scale accelerators, CPU runtime nodes, High speed swarmx interconnect, High speed data transfer of weights through memoryx interconnect
Qualify cluster networking solutions which consists of high-speed switches, routers and optics from various vendors
Qualify cluster security features including OS security, network security, cloud compliance user access and security certifications
Qualifications:
Bachelor's or master's degree in engineering in computer science, electrical, AI, data science of related field
10+ years of experience in testing one of areas like enterprise software, distributed systems, datacenter hardware and software
Experience working in large enterprise or cloud networking infrastructure, high speed switches, routers, firewalls
Experience in qualifying networking vendor platforms like Juniper, Arista or Cisco and network test equipment like Ixia/Spirent
Experience in Datacenter technology like BGP, ECN, PFC
Experience testing networking security, compliance and firewalls
Strong coding skills in one of the programming languages like python, golang or C/C++
Strong debugging skills to debug issues in large distributed systems, hardware, and software. Experience with debugging tools like gdb, strace, networking monitors
Strong understanding of operating systems internals like memory management, file system working, security basics and performance
Strong understanding of datacenter layout, device performance characteristics like PCIe, networking and storage
Experience with cloud technologies like AWS, kubernetes and dockers. Monitoring tools like grafana, prometheus is huge plus
Understanding and experience of ML model training and inference is a huge plus
Understand of ML hardware accelerators like GPU, custom accelerator ASIC is a huge plus
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nIn AI infrastructure organization, simplifying large hardware deployments with push button, single pane of glass for observability/monitoring and software capabilities for build-in resiliency are some of the key focus areas. As senior software development engineer in Test, we are looking for a candidate who can make a big impact on how we test and validate thousands of nodes in large deployments to ensure the cluster is 99.999% reliable. \n \n \nResponsibities: \n\n - You will be hired to innovate and execute tests on cutting edge AI infrastructure. Be a thinker, define optimized test strategies and methodologies. \n\n - Cerebras is growing and innovating at a rapid pace and so is the ML community and AI models. Be a quick learner, adapt to new technologies, and bring your expertise. We are looking to hire a team with a diverse skill set. \n\n - Deep understanding of how large-scale distributed ML training and inference works. Build a strong understanding of how to break these large distributed systems challenge into smaller components that can be unit tested\n\n\n\n - Automate first approach - In large scale deployment, automation drives efficiency and scalability. Aim for 100% automated tests to test all cluster features in areas of high availability, failure scenarios, performance, stress and security\n\n\n\n - Champion cluster security, reliability for uptime of 99.9999% and ease of use with observability.\n\n\n\n - Test all components of AI cluster including but not limited to cluster software involving kubernetes, prometheus and grafana. Cluster hardware components like ML wafer scale accelerators, CPU runtime nodes, High speed swarmx interconnect, High speed data transfer of weights through memoryx interconnect\n\n\n\n - Qualify cluster networking solutions which consists of high-speed switches, routers and optics from various vendors\n\n\n\n - Qualify cluster security features including OS security, network security, cloud compliance user access and security certifications\n\nQualifications:\n\n\n\n - Bachelor's or master's degree in engineering in computer science, electrical, AI, data science of related field \n\n - 10+ years of experience in testing one of areas like enterprise software, distributed systems, datacenter hardware and software\n\n\n\n - Experience working in large enterprise or cloud networking infrastructure, high speed switches, routers, firewalls\n\n\n\n - Experience in qualifying networking vendor platforms like Juniper, Arista or Cisco and network test equipment like Ixia/Spirent\n\n\n\n - Experience in Datacenter technology like BGP, ECN, PFC\n\n\n\n - Experience testing networking security, compliance and firewalls \n\n - Strong coding skills in one of the programming languages like python, golang or C/C++ \n\n - Strong debugging skills to debug issues in large distributed systems, hardware, and software. Experience with debugging tools like gdb, strace, networking monitors \n\n - Strong understanding of operating systems internals like memory management, file system working, security basics and performance\n\n\n\n - Strong understanding of datacenter layout, device performance characteristics like PCIe, networking and storage \n\n - Experience with cloud technologies like AWS, kubernetes and dockers. Monitoring tools like grafana, prometheus is huge plus \n\n - Understanding and experience of ML model training and inference is a huge plus \n\n - Understand of ML hardware accelerators like GPU, custom accelerator ASIC is a huge plus\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"79eec4ee-8c02-407a-899c-3848f7c2a8b8","title":"Full Stack Engineer - Console Team","department":"Software Engineering ","team":"Inference Service","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2026-07-17T00:37:15.148+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressRegion":"California ","addressCountry":"United States","addressLocality":"Sunnyvale "}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/79eec4ee-8c02-407a-899c-3848f7c2a8b8","applyUrl":"https://jobs.ashbyhq.com/cerebras/79eec4ee-8c02-407a-899c-3848f7c2a8b8/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
We’re hiring a full-stack engineer to build the critical parts of the Cerebras Developer Console — the primary interface developers and enterprises use to run and manage inference workloads.
This is a deeply technical, end-to-end role. You’ll build high-quality frontend systems (Next.js, TypeScript) and design backend services (GraphQL, Postgres, Redis) that power usage tracking, billing, quotas, and observability. The systems you build will operate at high scale, require careful data modeling, and balance real-time and batch processing. You’ll be expected to make strong architectural decisions and move quickly from idea to production.
You’ll join an existing, high-velocity team and take ownership of major platform areas such as billing, request logs, and metrics. The work directly impacts customer experience and revenue, and the expectations are correspondingly high.
We’re looking for someone who thrives in fast-moving environments, operates with urgency, and is comfortable navigating ambiguity while shipping high-quality systems.
What You’ll Do
Build and evolve core systems — design and implement APIs, services, and UI that power the Developer Console and scale with growing customer usage.
Make architectural decisions — define system boundaries, data models, and tradeoffs across real-time vs batch processing, performance, and cost.
Drive projects from 0 → 1 → scale — take ambiguous problems, define solutions, and deliver them to production.
Partner with product and design — shape developer-facing workflows and experiences.
What We’re Looking For
Technical depth in backend systems — strong fundamentals in APIs, data modeling, and distributed systems; experience with high-scale or real-time systems is a plus.
Full-stack capability — comfortable working across frontend and backend, with the ability to make pragmatic tradeoffs.
Strong technical judgment — you make sound architectural decisions and know when to optimize vs move fast.
Ability to operate without structure — you bring clarity to ambiguous problems and drive execution independently.
High standards for quality — you care about correctness, maintainability, and long-term system health.
Bias for action — you move quickly, unblock yourself and others, and focus on impact.
Experience in fast-moving environments — comfortable with shifting priorities and evolving scope.
Experience — typically 1-3 years of industry experience building and operating production systems.
Education — Bachelor’s or master's in computer science (or equivalent practical experience).
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nWe’re hiring a full-stack engineer to build the critical parts of the Cerebras Developer Console — the primary interface developers and enterprises use to run and manage inference workloads.\n\nThis is a deeply technical, end-to-end role. You’ll build high-quality frontend systems (Next.js, TypeScript) and design backend services (GraphQL, Postgres, Redis) that power usage tracking, billing, quotas, and observability. The systems you build will operate at high scale, require careful data modeling, and balance real-time and batch processing. You’ll be expected to make strong architectural decisions and move quickly from idea to production.\n\nYou’ll join an existing, high-velocity team and take ownership of major platform areas such as billing, request logs, and metrics. The work directly impacts customer experience and revenue, and the expectations are correspondingly high.\n\nWe’re looking for someone who thrives in fast-moving environments, operates with urgency, and is comfortable navigating ambiguity while shipping high-quality systems.\n\nWhat You’ll Do\n\n - Build and evolve core systems — design and implement APIs, services, and UI that power the Developer Console and scale with growing customer usage.\n\n - Make architectural decisions — define system boundaries, data models, and tradeoffs across real-time vs batch processing, performance, and cost.\n\n - Drive projects from 0 → 1 → scale — take ambiguous problems, define solutions, and deliver them to production.\n\n - Partner with product and design — shape developer-facing workflows and experiences.\n\nWhat We’re Looking For\n\n - Technical depth in backend systems — strong fundamentals in APIs, data modeling, and distributed systems; experience with high-scale or real-time systems is a plus.\n\n - Full-stack capability — comfortable working across frontend and backend, with the ability to make pragmatic tradeoffs.\n\n - Strong technical judgment — you make sound architectural decisions and know when to optimize vs move fast.\n\n - Ability to operate without structure — you bring clarity to ambiguous problems and drive execution independently.\n\n - High standards for quality — you care about correctness, maintainability, and long-term system health.\n\n - Bias for action — you move quickly, unblock yourself and others, and focus on impact.\n\n - Experience in fast-moving environments — comfortable with shifting priorities and evolving scope.\n\n - Experience — typically 1-3 years of industry experience building and operating production systems.\n\n - Education — Bachelor’s or master's in computer science (or equivalent practical experience).\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"084b4552-7d3a-491b-87ff-92e195aa2ef2","title":" Release Qualification Team Lead","department":"Software Engineering ","team":"Inference Service","employmentType":"FullTime","location":"Bengaluru, IND","secondaryLocations":[],"publishedAt":"2026-07-20T16:36:33.011+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressRegion":"Karnataka ","addressCountry":"India","addressLocality":"Bengaluru"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/084b4552-7d3a-491b-87ff-92e195aa2ef2","applyUrl":"https://jobs.ashbyhq.com/cerebras/084b4552-7d3a-491b-87ff-92e195aa2ef2/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
The Inference Service Quality team owns the confidence behind every release shipped across Cerebras Cloud, Inference Platform, and Inference API. We work closely with platform, infrastructure, ML systems, and product engineering teams to ensure that rapid iteration never comes at the expense of customer trust. Our environment spans distributed cloud systems, multi-region deployments, APIs, orchestration layers, and hardware-backed inference services.
Release velocity is high and the systems grow more complex every quarter. We need a leader who can turn release qualification from an ad hoc, reactive scramble into a predictable, owned discipline that scales with the business.
As the Release Qualification Team Lead, you will be the accountable owner for weekly end-to-end release qualification on behalf of our org, establishing it as a first-class, owned discipline. You will build and run a purpose-built release qualification team with planned triage capacity and the depth of context needed to triage, debug, and confidently decide what unblocks a release. You will own the full release qualification lifecycle — test planning, release planning, documentation, and tooling — turning hard-won knowledge into organized, accessible practice.
As the technical counterpart to the cross-org qualification team, you'll be the person who truly understands our tests and can speak for them. Success in this role depends on effective communication and close coordination across teams and time zones, keeping every stakeholder aligned through fast-moving release windows.
A central part of your charter is expanding end-to-end coverage across Cloud, Inference Platform, and Inference API — qualifying the steady stream of new Cerebras models, the new APIs that support them, and new cloud features, and driving qualification all the way through as the systems grow.
Drive weekly end-to-end release qualification as the accountable owner from our org.
Build and run a purpose-built release qualification team so triage capacity is planned, not scrambled — ensuring strong, predictable representation from our org rather than ad hoc pulls.
Own the full release qualification lifecycle: test planning, release planning, document
Own triage, debug, and escalation during release windows — including deciding what blocks a release and routing fixes to the right owners.
Drive expanded end-to-end coverage across Cloud, Inference Platform, and Inference API,e way through despite cross-org boundaries.
Partner with the cross-org release qualification team as the technical counterpart who actually understands our tests.
Distinguish real regressions from flakiness quickly, and keep a living record of what td who to escalate to.
Mentor engineers on triage, debugging practices, and qualification methodology.
7+ years of relevant industry experience in software integration, development, or quality engineering, including prior release qualification experience.
Proven ownership of end-to-end release or qualification processes for complex, distribu
Strong track record of debugging complex issues across distributed, scaled-out deployments under release-blocking time pressure.
Deep expertise in automation and programming using one or more languages such as Pythongn and build reusable test frameworks from the ground up.
Demonstrated ability to lead cross-functional initiatives spanning multiple orgs, product development, product management, and field teams.
Sound judgment on coverage trade-offs, risk-based prioritization, and go/no-go release
Excellent verbal and written communication skills, with experience presenting technical findings to both engineering and leadership audiences.
Strong organizational skills, ownership mindset, and ability to drive projects to compl
Experience leading and mentoring engineers across geographically dispersed teams and time zones.
Hands-on experience with ML workloads including LLM and/or multimodal training or inference.
Experience designing test strategies for distributed systems, cloud infrastructure, and
Experience with microservices deployment, debugging, and orchestration at scale.
Familiarity with hardware-backed inference services and the trade-offs of hardware/soft
Prior experience building or significantly shaping a team's quality engineering culture or test infrastructure.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n\nABOUT THE TEAM\n\nThe Inference Service Quality team owns the confidence behind every release shipped across Cerebras Cloud, Inference Platform, and Inference API. We work closely with platform, infrastructure, ML systems, and product engineering teams to ensure that rapid iteration never comes at the expense of customer trust. Our environment spans distributed cloud systems, multi-region deployments, APIs, orchestration layers, and hardware-backed inference services.\n\nRelease velocity is high and the systems grow more complex every quarter. We need a leader who can turn release qualification from an ad hoc, reactive scramble into a predictable, owned discipline that scales with the business.\n\n\nABOUT THE ROLE\n\nAs the Release Qualification Team Lead, you will be the accountable owner for weekly end-to-end release qualification on behalf of our org, establishing it as a first-class, owned discipline. You will build and run a purpose-built release qualification team with planned triage capacity and the depth of context needed to triage, debug, and confidently decide what unblocks a release. You will own the full release qualification lifecycle — test planning, release planning, documentation, and tooling — turning hard-won knowledge into organized, accessible practice.\n\nAs the technical counterpart to the cross-org qualification team, you'll be the person who truly understands our tests and can speak for them. Success in this role depends on effective communication and close coordination across teams and time zones, keeping every stakeholder aligned through fast-moving release windows.\n\nA central part of your charter is expanding end-to-end coverage across Cloud, Inference Platform, and Inference API — qualifying the steady stream of new Cerebras models, the new APIs that support them, and new cloud features, and driving qualification all the way through as the systems grow.\n\n\nRESPONSIBILITIES\n\n - Drive weekly end-to-end release qualification as the accountable owner from our org.\n\n - Build and run a purpose-built release qualification team so triage capacity is planned, not scrambled — ensuring strong, predictable representation from our org rather than ad hoc pulls.\n\n - Own the full release qualification lifecycle: test planning, release planning, document\n\n - Own triage, debug, and escalation during release windows — including deciding what blocks a release and routing fixes to the right owners.\n\n - Drive expanded end-to-end coverage across Cloud, Inference Platform, and Inference API,e way through despite cross-org boundaries.\n\n - Partner with the cross-org release qualification team as the technical counterpart who actually understands our tests.\n\n - Distinguish real regressions from flakiness quickly, and keep a living record of what td who to escalate to.\n\n - Mentor engineers on triage, debugging practices, and qualification methodology.\n\n\nSKILLS & QUALIFICATIONS\n\n - 7+ years of relevant industry experience in software integration, development, or quality engineering, including prior release qualification experience.\n\n - Proven ownership of end-to-end release or qualification processes for complex, distribu\n\n - Strong track record of debugging complex issues across distributed, scaled-out deployments under release-blocking time pressure.\n\n - Deep expertise in automation and programming using one or more languages such as Pythongn and build reusable test frameworks from the ground up.\n\n - Demonstrated ability to lead cross-functional initiatives spanning multiple orgs, product development, product management, and field teams.\n\n - Sound judgment on coverage trade-offs, risk-based prioritization, and go/no-go release\n\n - Excellent verbal and written communication skills, with experience presenting technical findings to both engineering and leadership audiences.\n\n - Strong organizational skills, ownership mindset, and ability to drive projects to compl\n\n - Experience leading and mentoring engineers across geographically dispersed teams and time zones.\n\n\nPREFERRED SKILLS & QUALIFICATIONS\n\n - Hands-on experience with ML workloads including LLM and/or multimodal training or inference.\n\n - Experience designing test strategies for distributed systems, cloud infrastructure, and\n\n - Experience with microservices deployment, debugging, and orchestration at scale.\n\n - Familiarity with hardware-backed inference services and the trade-offs of hardware/soft\n\n - Prior experience building or significantly shaping a team's quality engineering culture or test infrastructure.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"465e7d06-93c1-49e5-a2c9-7088d1bcda0a","title":"Deployment Manager – Global Data Center Build and Deploy","department":"Datacenters","team":"Datacenters","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[{"location":"Remote","address":null}],"publishedAt":"2026-07-20T19:39:30.152+00:00","isListed":true,"isRemote":true,"workplaceType":"Remote","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/465e7d06-93c1-49e5-a2c9-7088d1bcda0a","applyUrl":"https://jobs.ashbyhq.com/cerebras/465e7d06-93c1-49e5-a2c9-7088d1bcda0a/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
The Deployment Manager – Global Data Center Build and Deploy is responsible for the end-to-end execution of AI cluster deployments within large-scale data centers, specifically taking from facility ready for power and cooling to customer hand-off. This role leads rack integration, high-density inter-rack cabling, and close coordination with facilities, networking, and operations teams to deliver Cerebras Wafer Scale Engine based clusters safely, on schedule, and to strict quality standards.
The ideal candidate has deep experience deploying AI infrastructure, understands the operational demands of high-power, high-thermal-density environments, and excels at troubleshooting complex cabling and integration issues. This role requires providing directions to technicians on the Data Center floor, and resolve any issue blocking build and deploy in data centers. The role requires traveling and physically present at Data Center weeks at a time.
Lead deployment of AI clusters including Cerebras Wafer Scale Engine, high-speed switches, storage, and rack-level infrastructure
Coordinate rack integration of high-density compute, specialized racks, and associated power components (PDUs, busway drops)
Ensure deployment aligns with AI cluster architecture, topology, and scaling requirements
Manage installation of high-speed interconnect cabling (fiber and copper) supporting AI fabrics (east–west traffic) in Data Centers
Coordinate inter-rack and intra-rack cabling for AI clusters, including spine-leaf and pod-level designs
Ensure proper routing, airflow clearance, labeling, and testing of all AI-related cabling
Work closely with facilities teams on power capacity, cooling readiness, containment, and grounding for dense racks
Coordinate deployment sequencing with facility commissioning milestones
Validate white-space readiness before rack and cluster deployment
Provide directions to technicians on the data center floor.
Troubleshoot cabling, connectivity, and integration issues impacting AI cluster bring-up
Lead root-cause analysis for deployment blockers related to cabling, hardware placement, or facilities dependencies
Support validation, burn-in, and handoff of AI clusters to operations teams
Partner with network, server, AI platform, and operations teams to align on deployment plans and readiness
Manage multiple parallel AI cluster deployments across sites or availability zones
Communicate risks, dependencies, and milestones clearly to stakeholders
Ensure deployments follow company design standards, structured cabling best practices, and AI deployment playbooks
Validate as-built documentation, labeling accuracy, and deployment checklists
Maintain accurate records for cluster configuration, cabling, and deployment status
Enforce EHS, data center safety, and access control procedures during deployment
Ensure safe handling of heavy, high-power GPU equipment
Proactively identify and mitigate deployment and operational risks
Bachelor’s degree in Engineering, IT, or equivalent practical experience
10+ years of experience in data center deployments, infrastructure delivery, or integration roles
Ability to provide directions to technicians on data center floor.
Hands-on experience deploying hyperscale AI, ML, or HPC infrastructure
Strong experience with structured cabling in high-density environments, and troubleshooting
Proven ability to manage complex, cross-functional deployment programs
Familiarity with high-speed fabrics (e.g., InfiniBand, high-bandwidth Ethernet)
Experience with DCIM or deployment tracking systems
Strong attention to detail and operational rigor
Ability to perform under tight timelines and production constraints
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n\n\n\nTHE ROLE\n\nThe Deployment Manager – Global Data Center Build and Deploy is responsible for the end-to-end execution of AI cluster deployments within large-scale data centers, specifically taking from facility ready for power and cooling to customer hand-off. This role leads rack integration, high-density inter-rack cabling, and close coordination with facilities, networking, and operations teams to deliver Cerebras Wafer Scale Engine based clusters safely, on schedule, and to strict quality standards.\n\n\n\nThe ideal candidate has deep experience deploying AI infrastructure, understands the operational demands of high-power, high-thermal-density environments, and excels at troubleshooting complex cabling and integration issues. This role requires providing directions to technicians on the Data Center floor, and resolve any issue blocking build and deploy in data centers. The role requires traveling and physically present at Data Center weeks at a time.\n\n\n\n\nRESPONSIBILITIES \n\n\nAI CLUSTER DEPLOYMENT & RACK INTEGRATION\n\n - Lead deployment of AI clusters including Cerebras Wafer Scale Engine, high-speed switches, storage, and rack-level infrastructure\n\n - Coordinate rack integration of high-density compute, specialized racks, and associated power components (PDUs, busway drops)\n\n - Ensure deployment aligns with AI cluster architecture, topology, and scaling requirements\n\n\nHIGH-DENSITY INTER-RACK & INTRA-RACK CABLING\n\n - Manage installation of high-speed interconnect cabling (fiber and copper) supporting AI fabrics (east–west traffic) in Data Centers\n\n - Coordinate inter-rack and intra-rack cabling for AI clusters, including spine-leaf and pod-level designs\n\n - Ensure proper routing, airflow clearance, labeling, and testing of all AI-related cabling\n\n\nFACILITIES & INFRASTRUCTURE COORDINATION\n\n - Work closely with facilities teams on power capacity, cooling readiness, containment, and grounding for dense racks\n\n - Coordinate deployment sequencing with facility commissioning milestones\n\n - Validate white-space readiness before rack and cluster deployment\n\n - Provide directions to technicians on the data center floor.\n\n\nTROUBLESHOOTING & ISSUE RESOLUTION\n\n - Troubleshoot cabling, connectivity, and integration issues impacting AI cluster bring-up\n\n - Lead root-cause analysis for deployment blockers related to cabling, hardware placement, or facilities dependencies\n\n - Support validation, burn-in, and handoff of AI clusters to operations teams\n\n\nCROSS-FUNCTIONAL EXECUTION\n\n - Partner with network, server, AI platform, and operations teams to align on deployment plans and readiness\n\n - Manage multiple parallel AI cluster deployments across sites or availability zones\n\n - Communicate risks, dependencies, and milestones clearly to stakeholders\n\n\nQUALITY, STANDARDS & DOCUMENTATION\n\n - Ensure deployments follow company design standards, structured cabling best practices, and AI deployment playbooks\n\n - Validate as-built documentation, labeling accuracy, and deployment checklists\n\n - Maintain accurate records for cluster configuration, cabling, and deployment status\n\n\nSAFETY & RISK MANAGEMENT\n\n - Enforce EHS, data center safety, and access control procedures during deployment\n\n - Ensure safe handling of heavy, high-power GPU equipment\n\n - Proactively identify and mitigate deployment and operational risks\n\n\n\n\nQUALIFICATIONS\n\n - Bachelor’s degree in Engineering, IT, or equivalent practical experience\n\n - 10+ years of experience in data center deployments, infrastructure delivery, or integration roles\n\n - Ability to provide directions to technicians on data center floor.\n\n - Hands-on experience deploying hyperscale AI, ML, or HPC infrastructure\n\n - Strong experience with structured cabling in high-density environments, and troubleshooting\n\n - Proven ability to manage complex, cross-functional deployment programs\n\n - Familiarity with high-speed fabrics (e.g., InfiniBand, high-bandwidth Ethernet)\n\n - Experience with DCIM or deployment tracking systems\n\n - Strong attention to detail and operational rigor\n\n - Ability to perform under tight timelines and production constraints\n\n\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"156913ad-fcce-4551-b422-b5df5a9310fe","title":"Director, Intellectual Property Counsel","department":"Corporate","team":"Legal","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[{"location":"Remote","address":null}],"publishedAt":"2026-07-25T00:07:44.063+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressRegion":"California ","addressCountry":"United States","addressLocality":"Sunnyvale "}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/156913ad-fcce-4551-b422-b5df5a9310fe","applyUrl":"https://jobs.ashbyhq.com/cerebras/156913ad-fcce-4551-b422-b5df5a9310fe/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About the Role
Cerebras has built a breakthrough architecture that is unlocking new opportunities for the AI industry. As Director, IP, you will lead the development and execution of Cerebras’ global intellectual property strategy. You will partner with engineering, research, product, security, marketing, and executive leadership to build, protect, and leverage the company’s patent, trademark, copyright, trade secret, and open source assets in support of Cerebras’ AI hardware, software, cloud services, and strategic business initiatives.
This is a hands-on, business-facing role for an IP attorney who enjoys working directly with inventors and technical leaders building advanced AI infrastructure. You will identify high-value inventions, guide global filing strategy, manage outside prosecution counsel, support IP risk assessments, and advise on licensing, collaboration, supply chain, customer, and strategic transaction matters. The right candidate brings technical curiosity, practical judgment, and the ability to turn complex AI hardware, systems, software, and infrastructure issues into clear, actionable guidance.
Responsibilities
Develop and execute Cerebras’ enterprise intellectual property strategy aligned with product roadmap, business objectives, competitive positioning, and corporate growth.
Advise executive leadership on IP strategy, competitive landscape, IP risks, licensing opportunities, standards participation, and emerging AI legal developments.
Build and maintain an integrated IP portfolio spanning patents, trademarks, copyrights, trade secrets, domain names, and other proprietary assets.
Drive strategic invention harvesting and patent portfolio development across the full AI infrastructure stack.
Partner directly with engineers, researchers, product leaders, and executives to identify patentable innovation, improve invention disclosure quality, and align filing decisions with technical roadmaps and business priorities.
Manage U.S. and international patent preparation and prosecution, including directing outside counsel, reviewing applications and office action responses, setting claim strategy, and maintaining quality, cost, and timing discipline.
Build subject matter expertise in Cerebras' key technical areas and proactively identify portfolio opportunities tied to product releases, customer deployments, partnerships, competitive developments, and emerging standards.
Advise on intellectual property issues relating to generative AI, foundation models, and evolving legal and regulatory developments affecting AI technologies.
Support commercial, corporate, and product counsel on IP provisions in customer agreements, cloud and data center arrangements, supply chain and manufacturing relationships, university and research collaborations, licensing, and other strategic transactions.
Skills & Qualifications
J.D. from an accredited law school and active membership in at least one U.S. state bar; California bar membership is preferred.
Registration to practice before the U.S. Patent and Trademark Office.
10+ years of experience drafting and prosecuting patent applications, preferably with meaningful work in AI infrastructure, high-performance computing, semiconductors, electrical engineering, computer science, systems, networking, cloud infrastructure, or related areas.
Technical undergraduate degree or equivalent technical experience; electrical engineering, computer engineering, computer science, physics, or a closely related discipline preferred.
Ability to understand complex AI infrastructure, hardware, networking, cloud, and software systems and convert technical disclosures into strategically valuable patent claims.
Experience managing outside patent counsel and global patent portfolios with attention to quality, cost, timing, and business alignment.
Strong written and verbal communication skills, including the ability to explain patent strategy and risk clearly to engineers, business leaders, and executives.
Practical judgment, strong organization, attention to detail, and comfort managing multiple priorities in a fast-moving environment.
Collaborative working style, intellectual curiosity, and enthusiasm for advanced computing, AI infrastructure, and deep technology.
Preferred Experience
Prior in-house patent counsel experience at a high-growth technology company, semiconductor company, AI infrastructure provider, cloud provider, systems company, or advanced computing business.
Experience with patent portfolios involving AI infrastructure platforms, AI accelerators, high-performance computing systems, computer architecture, or data center infrastructure.
Experience counseling on patent issues in commercial transactions, strategic partnerships, standards organizations, university collaborations, open-source software, supply chain/manufacturing deals, or IP licensing.
Experience with patent assertions, invalidity and infringement analysis, or litigation support.
Foreign filing strategy experience, including PCT practice and prosecution before major non-U.S. patent offices.
Ability to build repeatable processes, dashboards, and executive-ready reporting for invention intake, portfolio review, outside counsel management, and IP risk tracking.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout the Role\n\nCerebras has built a breakthrough architecture that is unlocking new opportunities for the AI industry. As Director, IP, you will lead the development and execution of Cerebras’ global intellectual property strategy. You will partner with engineering, research, product, security, marketing, and executive leadership to build, protect, and leverage the company’s patent, trademark, copyright, trade secret, and open source assets in support of Cerebras’ AI hardware, software, cloud services, and strategic business initiatives.\n\nThis is a hands-on, business-facing role for an IP attorney who enjoys working directly with inventors and technical leaders building advanced AI infrastructure. You will identify high-value inventions, guide global filing strategy, manage outside prosecution counsel, support IP risk assessments, and advise on licensing, collaboration, supply chain, customer, and strategic transaction matters. The right candidate brings technical curiosity, practical judgment, and the ability to turn complex AI hardware, systems, software, and infrastructure issues into clear, actionable guidance.\n\nResponsibilities\n\n - Develop and execute Cerebras’ enterprise intellectual property strategy aligned with product roadmap, business objectives, competitive positioning, and corporate growth.\n\n - Advise executive leadership on IP strategy, competitive landscape, IP risks, licensing opportunities, standards participation, and emerging AI legal developments.\n\n - Build and maintain an integrated IP portfolio spanning patents, trademarks, copyrights, trade secrets, domain names, and other proprietary assets.\n\n - Drive strategic invention harvesting and patent portfolio development across the full AI infrastructure stack.\n\n - Partner directly with engineers, researchers, product leaders, and executives to identify patentable innovation, improve invention disclosure quality, and align filing decisions with technical roadmaps and business priorities.\n\n - Manage U.S. and international patent preparation and prosecution, including directing outside counsel, reviewing applications and office action responses, setting claim strategy, and maintaining quality, cost, and timing discipline.\n\n - Build subject matter expertise in Cerebras' key technical areas and proactively identify portfolio opportunities tied to product releases, customer deployments, partnerships, competitive developments, and emerging standards.\n\n - Advise on intellectual property issues relating to generative AI, foundation models, and evolving legal and regulatory developments affecting AI technologies.\n\n - Support commercial, corporate, and product counsel on IP provisions in customer agreements, cloud and data center arrangements, supply chain and manufacturing relationships, university and research collaborations, licensing, and other strategic transactions.\n\nSkills & Qualifications\n\n - J.D. from an accredited law school and active membership in at least one U.S. state bar; California bar membership is preferred.\n\n - Registration to practice before the U.S. Patent and Trademark Office.\n\n - 10+ years of experience drafting and prosecuting patent applications, preferably with meaningful work in AI infrastructure, high-performance computing, semiconductors, electrical engineering, computer science, systems, networking, cloud infrastructure, or related areas.\n\n - Technical undergraduate degree or equivalent technical experience; electrical engineering, computer engineering, computer science, physics, or a closely related discipline preferred.\n\n - Ability to understand complex AI infrastructure, hardware, networking, cloud, and software systems and convert technical disclosures into strategically valuable patent claims.\n\n - Experience managing outside patent counsel and global patent portfolios with attention to quality, cost, timing, and business alignment.\n\n - Strong written and verbal communication skills, including the ability to explain patent strategy and risk clearly to engineers, business leaders, and executives.\n\n - Practical judgment, strong organization, attention to detail, and comfort managing multiple priorities in a fast-moving environment.\n\n - Collaborative working style, intellectual curiosity, and enthusiasm for advanced computing, AI infrastructure, and deep technology.\n\nPreferred Experience\n\n - Prior in-house patent counsel experience at a high-growth technology company, semiconductor company, AI infrastructure provider, cloud provider, systems company, or advanced computing business.\n\n - Experience with patent portfolios involving AI infrastructure platforms, AI accelerators, high-performance computing systems, computer architecture, or data center infrastructure.\n\n - Experience counseling on patent issues in commercial transactions, strategic partnerships, standards organizations, university collaborations, open-source software, supply chain/manufacturing deals, or IP licensing.\n\n - Experience with patent assertions, invalidity and infringement analysis, or litigation support.\n\n - Foreign filing strategy experience, including PCT practice and prosecution before major non-U.S. patent offices.\n\n - Ability to build repeatable processes, dashboards, and executive-ready reporting for invention intake, portfolio review, outside counsel management, and IP risk tracking.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"63b9c135-ce5d-4898-8e4d-9422d39e4ca6","title":"Software Engineer, Cluster Deployment ","department":"Software Engineering ","team":"Cluster","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2026-07-23T10:34:15.819+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressRegion":"California ","addressCountry":"United States","addressLocality":"Sunnyvale "}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/63b9c135-ce5d-4898-8e4d-9422d39e4ca6","applyUrl":"https://jobs.ashbyhq.com/cerebras/63b9c135-ce5d-4898-8e4d-9422d39e4ca6/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About the Role
We build and operate the software systems that deploy, validate, and manage AI compute clusters across data centers worldwide for the world’s fastest AI Inference. Our work turns complex bare-metal infrastructure into repeatable, automated deployment flows spanning server provisioning, network configuration, Kubernetes bring-up, health validation, and operational handoff.
As a Software Engineer on the Cluster Deployment Automation team, you will help build the pushbutton tooling that makes large-scale cluster deployments faster, safer, and more reproducible. This role is designed for talented engineers passionate about learning through hands-on work with Python, Bash, Ansible, Linux, bare-metal servers, networking equipment, Kubernetes, and observability systems while learning how production AI infrastructure is built and operated at scale.
Responsibilities
Develop and maintain automation for deployment workflows, including provisioning, configuration, validation, and operational handoff.
Turn manual deployment steps into tested, repeatable pushbutton workflows.
Participate in hands-on cluster deployments to build practical debugging and operational expertise.
Troubleshoot issues across Linux systems, bare-metal servers, networking, storage, Kubernetes, and connectivity.
Contribute to infrastructure-as-code and GitOps workflows using tools such as Terraform, Ansible, pull requests, and code review.
Add health checks, observability, dashboards, and validation logic to improve deployment reliability.
Partner with networking, infrastructure, security, and operations teams to deliver secure and reproducible data center deployments.
Basic Qualifications
2+ years of mid- to large-scale data center deployment
Strong fundamentals in Python and Bash, with the ability to write scripts and small programs.
Basic Linux experience, including command-line usage, processes, filesystems, and disk troubleshooting.
Working knowledge of Git, including branching, commits, pull requests, and code review.
CS, ECE, or related technical degree, or equivalent practical experience.
Curiosity, strong problem-solving instincts, and willingness to work hands-on with real infrastructure.
Preferred Qualifications
Networking fundamentals, including VLANs and routing basics; exposure to BGP, switch configuration, or Arista EOS automation is a plus.
Kubernetes experience or familiarity.
Infrastructure-as-code and GitOps experience, including Terraform, Ansible, and PR-based change control.
Bare-metal provisioning concepts such as PXE, DHCP, iPXE, Redfish, IPMI, and BMC management.
Observability experience with Prometheus or Grafana.
API design and client-server architecture.
Automation side projects or open-source contributions.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout the Role\n\nWe build and operate the software systems that deploy, validate, and manage AI compute clusters across data centers worldwide for the world’s fastest AI Inference. Our work turns complex bare-metal infrastructure into repeatable, automated deployment flows spanning server provisioning, network configuration, Kubernetes bring-up, health validation, and operational handoff.\n\nAs a Software Engineer on the Cluster Deployment Automation team, you will help build the pushbutton tooling that makes large-scale cluster deployments faster, safer, and more reproducible. This role is designed for talented engineers passionate about learning through hands-on work with Python, Bash, Ansible, Linux, bare-metal servers, networking equipment, Kubernetes, and observability systems while learning how production AI infrastructure is built and operated at scale.\n\nResponsibilities\n\n - Develop and maintain automation for deployment workflows, including provisioning, configuration, validation, and operational handoff.\n\n - Turn manual deployment steps into tested, repeatable pushbutton workflows.\n\n - Participate in hands-on cluster deployments to build practical debugging and operational expertise.\n\n - Troubleshoot issues across Linux systems, bare-metal servers, networking, storage, Kubernetes, and connectivity.\n\n - Contribute to infrastructure-as-code and GitOps workflows using tools such as Terraform, Ansible, pull requests, and code review.\n\n - Add health checks, observability, dashboards, and validation logic to improve deployment reliability.\n\n - Partner with networking, infrastructure, security, and operations teams to deliver secure and reproducible data center deployments.\n\nBasic Qualifications\n\n - 2+ years of mid- to large-scale data center deployment \n\n - Strong fundamentals in Python and Bash, with the ability to write scripts and small programs.\n\n - Basic Linux experience, including command-line usage, processes, filesystems, and disk troubleshooting.\n\n - Working knowledge of Git, including branching, commits, pull requests, and code review.\n\n - CS, ECE, or related technical degree, or equivalent practical experience.\n\n - Curiosity, strong problem-solving instincts, and willingness to work hands-on with real infrastructure.\n\nPreferred Qualifications\n\n - Networking fundamentals, including VLANs and routing basics; exposure to BGP, switch configuration, or Arista EOS automation is a plus.\n\n - Kubernetes experience or familiarity.\n\n - Infrastructure-as-code and GitOps experience, including Terraform, Ansible, and PR-based change control.\n\n - Bare-metal provisioning concepts such as PXE, DHCP, iPXE, Redfish, IPMI, and BMC management.\n\n - Observability experience with Prometheus or Grafana.\n\n - API design and client-server architecture.\n\n - Automation side projects or open-source contributions.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"3fb6d1f7-a45c-4827-87ac-e0f7944b6350","title":"Director/Sr. Manager, AI Inference Model Scaling","department":"Software Engineering ","team":"Voyager","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2026-07-23T17:02:04.130+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressRegion":"California ","addressCountry":"United States","addressLocality":"Sunnyvale "}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/3fb6d1f7-a45c-4827-87ac-e0f7944b6350","applyUrl":"https://jobs.ashbyhq.com/cerebras/3fb6d1f7-a45c-4827-87ac-e0f7944b6350/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Sunnyvale, CA or Toronto, Canada (Hybrid)
About the Team
The Inference Model Scaling team enables state-of-the-art foundation models and generative AI workloads to run efficiently on Cerebras' Wafer-Scale Engine (WSE). We build the compiler frontend, model transformation pipeline, graph optimization infrastructure, high-performance kernel enablement, and runtime integration that together make next-generation AI models execute with industry-leading performance.
The team works at the intersection of machine learning frameworks, compiler technologies, distributed systems, hardware architecture, and model optimization. We collaborate closely with hardware architects, runtime engineers, cloud platform teams, AI researchers, and strategic customers to rapidly bring new model architectures into production.
About the Role
We're looking for an experienced engineering leader to build and scale our Inference Model Scaling organization.
You will define the technical vision, organizational strategy, and execution roadmap for a globally distributed engineering team responsible for enabling the latest foundation models on Cerebras hardware. You will lead the engineering organization responsible for ML model compilation and optimization as well as development of high-performance kernels.
This role combines deep technical leadership with organizational excellence. You will partner across compiler, runtime, cloud infrastructure, hardware architecture, product management, and AI research teams while helping shape the future of AI inference at Cerebras.
Responsibilities
Technical Leadership
Define the technical roadmap and strategy for the team.
Establish technical direction across multiple teams and engineering leaders.
Lead design reviews and establish engineering standards.
Drive support for emerging LLM architectures and inference workloads.
Team Leadership
Hire, mentor, and grow a high-performing engineering team.
Develop future technical leaders and managers.
Drive organizational planning, headcount strategy, and investment priorities.
Foster a strong engineering culture focused on execution, quality, and innovation.
Scale engineering processes while maintaining execution velocity.
Cross-Functional Collaboration
Partner with Cloud Platform, ML, and Hardware teams in planning and delivering for end-to-end service enablement in Cloud and On-Premise settings
Work with Product Management to prioritize model enablement and customer needs.
Collaborate closely with customers and solution architects on new model bring-up.
Influence future hardware/software co-design through ML model enablement and optimization insights.
Delivery & Execution
Own planning, prioritization, and execution across multiple concurrent initiatives.
Balance rapid model support with long-term ML Compiler architecture.
Drive predictable delivery for strategic customer commitments.
Required Qualifications
BS, MS, or PhD in Computer Science, Computer Engineering or related field.
12+ years building compiler, ML systems, or infrastructure software.
5+ years leading engineering teams.
Deep experience with modern compiler infrastructure (LLVM, MLIR, XLA, TVM, Torch FX, or similar).
Strong understanding of graph compilation and optimization.
Experience with Python and C++.
Experience delivering production-quality software.
Strong communication and cross-functional leadership skills.
Preferred Qualifications
Experience building compiler frontends for AI accelerators.
Experience supporting PyTorch, JAX, TensorFlow, or ONNX.
Experience with LLM inference or training systems.
Familiarity with distributed compilation.
Experience working with hardware architects.
Experience leading teams through rapid growth.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nSunnyvale, CA or Toronto, Canada (Hybrid)\n\nAbout the Team\n\nThe Inference Model Scaling team enables state-of-the-art foundation models and generative AI workloads to run efficiently on Cerebras' Wafer-Scale Engine (WSE). We build the compiler frontend, model transformation pipeline, graph optimization infrastructure, high-performance kernel enablement, and runtime integration that together make next-generation AI models execute with industry-leading performance.\n\nThe team works at the intersection of machine learning frameworks, compiler technologies, distributed systems, hardware architecture, and model optimization. We collaborate closely with hardware architects, runtime engineers, cloud platform teams, AI researchers, and strategic customers to rapidly bring new model architectures into production.\n\nAbout the Role\n\nWe're looking for an experienced engineering leader to build and scale our Inference Model Scaling organization.\n\nYou will define the technical vision, organizational strategy, and execution roadmap for a globally distributed engineering team responsible for enabling the latest foundation models on Cerebras hardware. You will lead the engineering organization responsible for ML model compilation and optimization as well as development of high-performance kernels.\n\nThis role combines deep technical leadership with organizational excellence. You will partner across compiler, runtime, cloud infrastructure, hardware architecture, product management, and AI research teams while helping shape the future of AI inference at Cerebras.\n\nResponsibilities\n\nTechnical Leadership\n\n - Define the technical roadmap and strategy for the team.\n\n - Establish technical direction across multiple teams and engineering leaders.\n\n - Lead design reviews and establish engineering standards.\n\n - Drive support for emerging LLM architectures and inference workloads.\n\nTeam Leadership\n\n - Hire, mentor, and grow a high-performing engineering team.\n\n - Develop future technical leaders and managers.\n\n - Drive organizational planning, headcount strategy, and investment priorities.\n\n - Foster a strong engineering culture focused on execution, quality, and innovation.\n\n - Scale engineering processes while maintaining execution velocity.\n\nCross-Functional Collaboration\n\n - Partner with Cloud Platform, ML, and Hardware teams in planning and delivering for end-to-end service enablement in Cloud and On-Premise settings\n\n - Work with Product Management to prioritize model enablement and customer needs.\n\n - Collaborate closely with customers and solution architects on new model bring-up.\n\n - Influence future hardware/software co-design through ML model enablement and optimization insights.\n\nDelivery & Execution\n\n - Own planning, prioritization, and execution across multiple concurrent initiatives.\n\n - Balance rapid model support with long-term ML Compiler architecture.\n\n - Drive predictable delivery for strategic customer commitments.\n\nRequired Qualifications\n\n - BS, MS, or PhD in Computer Science, Computer Engineering or related field.\n\n - 12+ years building compiler, ML systems, or infrastructure software.\n\n - 5+ years leading engineering teams.\n\n - Deep experience with modern compiler infrastructure (LLVM, MLIR, XLA, TVM, Torch FX, or similar).\n\n - Strong understanding of graph compilation and optimization.\n\n - Experience with Python and C++.\n\n - Experience delivering production-quality software.\n\n - Strong communication and cross-functional leadership skills.\n\nPreferred Qualifications\n\n - Experience building compiler frontends for AI accelerators.\n\n - Experience supporting PyTorch, JAX, TensorFlow, or ONNX.\n\n - Experience with LLM inference or training systems.\n\n - Familiarity with distributed compilation.\n\n - Experience working with hardware architects.\n\n - Experience leading teams through rapid growth.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"9c7da4b8-446b-4bf2-8d07-23241590bf2e","title":"Kernel Engineer - New Grad","department":"University Departments","team":"New Grads","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2026-07-23T19:33:16.660+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressRegion":"California ","addressCountry":"United States","addressLocality":"Sunnyvale "}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/9c7da4b8-446b-4bf2-8d07-23241590bf2e","applyUrl":"https://jobs.ashbyhq.com/cerebras/9c7da4b8-446b-4bf2-8d07-23241590bf2e/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
As a Kernel Engineer at Cerebras, you will develop high-performance software at the intersection of hardware and software for cutting-edge artificial intelligence and high-performance computing workloads.
You will help implement, optimize, and validate machine learning and linear algebra operations for the Cerebras Wafer-Scale Engine, our custom massively parallel processor architecture. Working alongside experienced kernel, compiler, performance, and hardware engineers, you will learn how algorithms are mapped to specialized hardware and contribute to software that maximizes compute utilization and system performance.
You will be part of a team responsible for the design, development, performance tuning, and validation of foundational ML and HPC kernels. This is an excellent opportunity for a new graduate who is interested in computer architecture, parallel programming, low-level software, and machine learning systems.
Help design and implement machine learning and linear algebra kernels for the Cerebras Wafer-Scale Engine.
Develop and debug high-performance kernel routines using low-level programming techniques and the Cerebras Software Language, a custom C-like language.
Apply parallel programming algorithms to map computational workloads efficiently onto the Cerebras architecture.
Use mathematical analysis, performance data, and profiling tools to evaluate kernel behavior and inform design decisions.
Identify and investigate correctness, performance, and hardware utilization issues.
Develop unit tests and system-level validation methodologies to verify the functionality and performance of kernel libraries.
Collaborate with kernel, compiler, performance, and hardware engineers to improve software and system performance.
Study emerging machine learning workloads and contribute to the evolution of the kernel library.
Participate in code reviews, technical discussions, and software development processes.
Build an understanding of the Cerebras architecture, instruction set, memory system, and communication model.
Bachelor’s, Master’s, or PhD in Computer Science, Computer Engineering, Electrical Engineering, Mathematics, or a related field.
Strong programming fundamentals in C++ and familiarity with Python.
Understanding of foundational computer architecture concepts such as processors, memory hierarchies, instruction execution, or data movement.
Knowledge of data structures, algorithms, and software development fundamentals.
Experience debugging software through coursework, internships, research, co-op placements, or technical projects.
Strong analytical and problem-solving skills.
Interest in low-level software, parallel computing, performance optimization, or hardware/software co-design.
Ability to learn unfamiliar systems and collaborate effectively within a technical team.
Research, internships, or projects involving kernel development, compilers, computer architecture, HPC, or systems programming.
Familiarity with parallel algorithms, multithreaded programming, or distributed memory systems.
Exposure to programming accelerators such as GPUs, FPGAs, or other specialized processors.
Experience with low-level programming, assembly language, CUDA, OpenCL, or a domain-specific language.
Familiarity with machine learning concepts, neural networks, or frameworks such as PyTorch or TensorFlow.
Exposure to numerical computing, linear algebra, or HPC kernels.
Experience using profiling, benchmarking, or performance analysis tools.
Familiarity with library or API development practices.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n\nABOUT THE ROLE\n\nAs a Kernel Engineer at Cerebras, you will develop high-performance software at the intersection of hardware and software for cutting-edge artificial intelligence and high-performance computing workloads.\n\nYou will help implement, optimize, and validate machine learning and linear algebra operations for the Cerebras Wafer-Scale Engine, our custom massively parallel processor architecture. Working alongside experienced kernel, compiler, performance, and hardware engineers, you will learn how algorithms are mapped to specialized hardware and contribute to software that maximizes compute utilization and system performance.\n\nYou will be part of a team responsible for the design, development, performance tuning, and validation of foundational ML and HPC kernels. This is an excellent opportunity for a new graduate who is interested in computer architecture, parallel programming, low-level software, and machine learning systems.\n\n\n\n\nRESPONSIBILITIES\n\n - Help design and implement machine learning and linear algebra kernels for the Cerebras Wafer-Scale Engine.\n\n - Develop and debug high-performance kernel routines using low-level programming techniques and the Cerebras Software Language, a custom C-like language.\n\n - Apply parallel programming algorithms to map computational workloads efficiently onto the Cerebras architecture.\n\n - Use mathematical analysis, performance data, and profiling tools to evaluate kernel behavior and inform design decisions.\n\n - Identify and investigate correctness, performance, and hardware utilization issues.\n\n - Develop unit tests and system-level validation methodologies to verify the functionality and performance of kernel libraries.\n\n - Collaborate with kernel, compiler, performance, and hardware engineers to improve software and system performance.\n\n - Study emerging machine learning workloads and contribute to the evolution of the kernel library.\n\n - Participate in code reviews, technical discussions, and software development processes.\n\n - Build an understanding of the Cerebras architecture, instruction set, memory system, and communication model.\n\n\nMINIMUM SKILLS & QUALIFICATIONS\n\n - Bachelor’s, Master’s, or PhD in Computer Science, Computer Engineering, Electrical Engineering, Mathematics, or a related field.\n\n - Strong programming fundamentals in C++ and familiarity with Python.\n\n - Understanding of foundational computer architecture concepts such as processors, memory hierarchies, instruction execution, or data movement.\n\n - Knowledge of data structures, algorithms, and software development fundamentals.\n\n - Experience debugging software through coursework, internships, research, co-op placements, or technical projects.\n\n - Strong analytical and problem-solving skills.\n\n - Interest in low-level software, parallel computing, performance optimization, or hardware/software co-design.\n\n - Ability to learn unfamiliar systems and collaborate effectively within a technical team.\n\n\nPREFERRED SKILLS & QUALIFICATIONS\n\n - Research, internships, or projects involving kernel development, compilers, computer architecture, HPC, or systems programming.\n\n - Familiarity with parallel algorithms, multithreaded programming, or distributed memory systems.\n\n - Exposure to programming accelerators such as GPUs, FPGAs, or other specialized processors.\n\n - Experience with low-level programming, assembly language, CUDA, OpenCL, or a domain-specific language.\n\n - Familiarity with machine learning concepts, neural networks, or frameworks such as PyTorch or TensorFlow.\n\n - Exposure to numerical computing, linear algebra, or HPC kernels.\n\n - Experience using profiling, benchmarking, or performance analysis tools.\n\n - Familiarity with library or API development practices.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"ddc0eea7-3d35-41b5-98de-8978b1c7cdcf","title":"AI Inference Core - Senior SW Engineer for Platform & DevOps","department":"Software Engineering ","team":"Inference Core","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[{"location":"Toronto, CAN","address":{"postalAddress":{"addressRegion":"Ontario ","addressCountry":"Canada","addressLocality":"Toronto "}}}],"publishedAt":"2026-09-03T19:24:25.946+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressRegion":"California ","addressCountry":"United States","addressLocality":"Sunnyvale "}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/ddc0eea7-3d35-41b5-98de-8978b1c7cdcf","applyUrl":"https://jobs.ashbyhq.com/cerebras/ddc0eea7-3d35-41b5-98de-8978b1c7cdcf/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
The Core Infrastructure team builds the software systems that power engineering workflows across Cerebras.
Our infrastructure coordinates complex work across machines, clusters, development environments, and hardware systems. We build orchestration frameworks, execution engines, scheduling systems, test infrastructure, developer tools, and reusable software platforms that allow engineers to build, test, qualify, and deliver software reliably at scale.
These systems are primarily built in Python, but the work goes far beyond scripting or automation. Our frameworks act as the control plane for distributed workflows, managing resources, execution state, concurrency, failures, retries, dependencies, and observability across large and complex environments.
We are hiring a Software Engineer to build and operate the platform layer behind Cerebras engineering infrastructure.
You will work on CI/CD systems, Kubernetes, deployment automation, cloud and on-premises infrastructure, developer environments, artifact management, and observability. You will help make the systems engineers depend on reliable, scalable, and easy to operate.
This is an engineering-focused infrastructure role rather than a primarily ticket-driven operations position. You will automate repeated work, debug failures across system boundaries, and turn operational problems into durable software and platform improvements.
We value strong systems fundamentals, independent problem solving, and sound engineering judgment more than familiarity with any particular infrastructure product.
Design, build, and maintain CI/CD systems supporting build, test, integration, qualification, and release workflows.
Build and operate Kubernetes-based platforms and services used by engineering teams across Cerebras.
Develop deployment systems, internal tools, and self-service workflows that make infrastructure changes repeatable, reviewable, and safe.
Improve infrastructure reliability, capacity, performance, cost efficiency, monitoring, and operational readiness.
Debug issues spanning CI pipelines, Kubernetes workloads, networking, storage, authentication, operating systems, and distributed applications.
Perform root-cause analysis and implement lasting fixes rather than relying on repeated manual intervention.
Partner with software, IT, security, networking, release, and developer-productivity teams to deliver scalable infrastructure solutions.
5+ years of professional experience in platform engineering, DevOps, infrastructure engineering, site reliability engineering, or software engineering.
Hands-on experience building or maintaining CI/CD pipelines and automated software-delivery workflows.
Experience deploying and operating services using Kubernetes and containerized environments.
Experience with a major cloud platform, preferably AWS, and programmatic infrastructure provisioning.
Strong understanding of Linux or Unix operating-system fundamentals.
Understanding of networking concepts such as DNS, routing, load balancing, proxies, ports, TLS, and service connectivity.
Proficiency in Python, Shell, or another language used to build infrastructure automation and operational tooling.
Experience with monitoring, logging, alerting, dashboards, and incident investigation.
Strong debugging and problem-solving skills, including the ability to investigate issues spanning applications, infrastructure, networking, and operating systems.
Experience with infrastructure-as-code tools, specifically Terraform.
Experience with Kubernetes controllers, operators, custom resources, Helm, Argo CD, or similar platform technologies.
Experience managing artifact repositories, package registries, build caches, or software-distribution infrastructure.
Familiarity with build systems, dependency management, and reproducible-build practices.
Experience supporting hybrid environments spanning cloud infrastructure, on-premises systems, and specialized hardware.
Experience with identity and access management, secrets, certificates, TLS, or mTLS.
Experience building internal developer platforms or self-service infrastructure products.
BS/MS in Computer Science or a related field, or equivalent practical experience.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n\nABOUT THE TEAM\n\nThe Core Infrastructure team builds the software systems that power engineering workflows across Cerebras.\n\nOur infrastructure coordinates complex work across machines, clusters, development environments, and hardware systems. We build orchestration frameworks, execution engines, scheduling systems, test infrastructure, developer tools, and reusable software platforms that allow engineers to build, test, qualify, and deliver software reliably at scale.\n\nThese systems are primarily built in Python, but the work goes far beyond scripting or automation. Our frameworks act as the control plane for distributed workflows, managing resources, execution state, concurrency, failures, retries, dependencies, and observability across large and complex environments.\n\n\n\n\n\nABOUT THE ROLE\n\nWe are hiring a Software Engineer to build and operate the platform layer behind Cerebras engineering infrastructure.\n\nYou will work on CI/CD systems, Kubernetes, deployment automation, cloud and on-premises infrastructure, developer environments, artifact management, and observability. You will help make the systems engineers depend on reliable, scalable, and easy to operate.\n\nThis is an engineering-focused infrastructure role rather than a primarily ticket-driven operations position. You will automate repeated work, debug failures across system boundaries, and turn operational problems into durable software and platform improvements.\n\nWe value strong systems fundamentals, independent problem solving, and sound engineering judgment more than familiarity with any particular infrastructure product.\n\n\n\n\nRESPONSIBILITIES\n\n - Design, build, and maintain CI/CD systems supporting build, test, integration, qualification, and release workflows.\n\n - Build and operate Kubernetes-based platforms and services used by engineering teams across Cerebras.\n\n - Develop deployment systems, internal tools, and self-service workflows that make infrastructure changes repeatable, reviewable, and safe.\n\n - Improve infrastructure reliability, capacity, performance, cost efficiency, monitoring, and operational readiness.\n\n - Debug issues spanning CI pipelines, Kubernetes workloads, networking, storage, authentication, operating systems, and distributed applications.\n\n - Perform root-cause analysis and implement lasting fixes rather than relying on repeated manual intervention.\n\n - Partner with software, IT, security, networking, release, and developer-productivity teams to deliver scalable infrastructure solutions.\n\n\nSKILLS & QUALIFICATIONS\n\n - 5+ years of professional experience in platform engineering, DevOps, infrastructure engineering, site reliability engineering, or software engineering.\n\n - Hands-on experience building or maintaining CI/CD pipelines and automated software-delivery workflows.\n\n - Experience deploying and operating services using Kubernetes and containerized environments.\n\n - Experience with a major cloud platform, preferably AWS, and programmatic infrastructure provisioning.\n\n - Strong understanding of Linux or Unix operating-system fundamentals.\n\n - Understanding of networking concepts such as DNS, routing, load balancing, proxies, ports, TLS, and service connectivity.\n\n - Proficiency in Python, Shell, or another language used to build infrastructure automation and operational tooling.\n\n - Experience with monitoring, logging, alerting, dashboards, and incident investigation.\n\n - Strong debugging and problem-solving skills, including the ability to investigate issues spanning applications, infrastructure, networking, and operating systems.\n\n\nPREFERRED SKILLS & QUALIFICATIONS\n\n - Experience with infrastructure-as-code tools, specifically Terraform.\n\n - Experience with Kubernetes controllers, operators, custom resources, Helm, Argo CD, or similar platform technologies.\n\n - Experience managing artifact repositories, package registries, build caches, or software-distribution infrastructure.\n\n - Familiarity with build systems, dependency management, and reproducible-build practices.\n\n - Experience supporting hybrid environments spanning cloud infrastructure, on-premises systems, and specialized hardware.\n\n - Experience with identity and access management, secrets, certificates, TLS, or mTLS.\n\n - Experience building internal developer platforms or self-service infrastructure products.\n\n - BS/MS in Computer Science or a related field, or equivalent practical experience.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"af87f29d-7ae1-4306-b6b0-61b21971b456","title":"AI Inference Core - SDET Technical Lead, Release Integration Testing","department":"Software Engineering ","team":"Inference Core","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2026-09-03T19:22:52.625+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressRegion":"California ","addressCountry":"United States","addressLocality":"Sunnyvale "}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/af87f29d-7ae1-4306-b6b0-61b21971b456","applyUrl":"https://jobs.ashbyhq.com/cerebras/af87f29d-7ae1-4306-b6b0-61b21971b456/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
We are looking for a hands-on SDET Technical Lead to establish and lead Release Integration Testing within Release & Feature Qualification for AI Inference Core.
The Production Engine for Inference Core — turning integrated features into reliable production releases.
You will define the quality strategy across the pre-release and release cycle, from feature and model integration through branch stability, release qualification, deployment, and post-release learning. You will work across AI frameworks, runtime, compiler, kernels, distributed systems, infrastructure, and hardware to make release risk visible and actionable.
This is a technical-leadership role, not a coordination-only position. You will design test architecture, lead difficult debugging and release decisions, mentor engineers, and write software and automation alongside the team.
Release Integration Testing (RIT) is the bridge between feature qualification and release qualification. Feature teams retain ownership of feature design, feature-level qualification, and feature regression. Release Integration Testing owns inference-core integration strategy, inference-path readiness approval, integrated cross-stack validation, and first-pass rollout triage.
Dedicated Release Integration Testing ownership: Engage before feature qualification completes while keeping the boundary clear: feature teams own feature behavior and qualification; Release Integration Testing owns integration strategy, readiness approval, integrated validation, and first-pass rollout triage.
Inference-path readiness gate: Require evidence across unit, simulation, benchmark, feature, and integration testing, with explicit coverage gaps before release entry.
Cross-stack test strategy: Define risk-based E2E and regression coverage for features spanning components, organizations, software layers, infrastructure, and hardware.
Branch and rollout leadership: Establish measurable health standards for master and release branches, and coordinate inference-impacting rollout across multiple product and release projects.
Hands-on technical authority: Lead through code, test architecture, difficult debugging, quality metrics, and evidence-based release decisions.
Team multiplier: Raise the technical bar, mentor engineers, and align feature, infrastructure, integration, qualification, and release teams.
Define the Release Integration Testing strategy, engagement criteria, ownership boundaries, entry and exit criteria, coverage expectations, and escalation thresholds for AI Inference Core.
Engage early on high-risk inference changes; identify dependencies and interaction risks across runtime, host, device programming, memory, scheduling, model execution, infrastructure, and hardware.
Own the inference-path readiness gate by reviewing unit, simulation, benchmark, feature-test, and integration evidence, documenting gaps, and approving integration readiness before release entry.
Lead integrated inference E2E validation across features and the cloud-to-wafer stack; promote durable feature tests and add risk-based scenarios to release regression.
Improve master and release-branch stability through actionable health metrics, failure classification, release-quality reporting, dashboards, qualification workflows, and release pipelines.
Lead first-pass regression and rollout triage, coordinate owners through resolution, drive RCA, place missing coverage at the correct layer, and plan rollout across multiple product and release projects.
Partner with and mentor SDETs, feature teams, Integration, Core Infra, release owners, and deployment teams; between active engagements, advance automation efficiency, diagnostics, probes, and roadmap test planning.
Strong software-engineering fundamentals and programming ability in Python Go, or a similar language.
Demonstrated technical leadership in software quality, test infrastructure, systems validation, release engineering, or complex software integration.
Experience designing automation and test architecture for distributed, systems-level, infrastructure, or AI software.
Proven ability to break down ambiguous cross-stack failures, form hypotheses, gather evidence, and drive issues to resolution.
Strong understanding of risk-based testing, release readiness, regression strategy, failure analysis, and quality metrics.
Ability to influence and align multiple engineering teams without relying solely on organizational authority.
Clear communication and sound judgment during high-pressure release situations, including the ability to explain technical risk to engineering and leadership audiences.
Experience with software/hardware co-design, hardware accelerators, compilers, kernels, runtimes, or low-level systems.
Experience with AI infrastructure, model deployment, LLMs, multimodal workloads, or large-scale compute clusters.
Experience building test frameworks, distributed test systems, release pipelines, dashboards, or internal developer tooling.
Experience with performance testing, profiling, observability, fault injection, reliability, or production failure analysis.
Experience in a startup or similarly fast-moving, resource-constrained engineering environment.
Track record of taking a quality or release capability from zero to one and scaling it across teams.
Familiarity with containers, cluster orchestration, cloud infrastructure, CI/CD, or high-performance computing.
Release readiness is based on explicit criteria and high-signal evidence rather than intuition.
Fewer inference-path integration defects are first discovered in final release qualification or production.
Cross-component risks are found earlier, debug cycles are shorter, and coverage ownership is explicit.
Master and release-branch health is measurable, actionable, and steadily improving.
Test automation and release infrastructure shorten feedback loops without sacrificing signal quality.
Release metrics and reports drive clear decisions, ownership, and predictable feature rollout.
Engineers across the organization are more effective because Release Integration Testing provides strong technical direction, tooling, and mentorship.
This role requires in-office presence, at least three days per week. Fully remote work is not available.
Office locations: Sunnyvale, CA or Toronto, ON.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n\nABOUT THE ROLE\n\nWe are looking for a hands-on SDET Technical Lead to establish and lead Release Integration Testing within Release & Feature Qualification for AI Inference Core.\n\nThe Production Engine for Inference Core — turning integrated features into reliable production releases.\n\nYou will define the quality strategy across the pre-release and release cycle, from feature and model integration through branch stability, release qualification, deployment, and post-release learning. You will work across AI frameworks, runtime, compiler, kernels, distributed systems, infrastructure, and hardware to make release risk visible and actionable.\n\nThis is a technical-leadership role, not a coordination-only position. You will design test architecture, lead difficult debugging and release decisions, mentor engineers, and write software and automation alongside the team.\n\nRelease Integration Testing (RIT) is the bridge between feature qualification and release qualification. Feature teams retain ownership of feature design, feature-level qualification, and feature regression. Release Integration Testing owns inference-core integration strategy, inference-path readiness approval, integrated cross-stack validation, and first-pass rollout triage.\n\n\n\n\nWHAT MAKES THIS ROLE DISTINCT\n\n - Dedicated Release Integration Testing ownership: Engage before feature qualification completes while keeping the boundary clear: feature teams own feature behavior and qualification; Release Integration Testing owns integration strategy, readiness approval, integrated validation, and first-pass rollout triage.\n\n - Inference-path readiness gate: Require evidence across unit, simulation, benchmark, feature, and integration testing, with explicit coverage gaps before release entry.\n\n - Cross-stack test strategy: Define risk-based E2E and regression coverage for features spanning components, organizations, software layers, infrastructure, and hardware.\n\n - Branch and rollout leadership: Establish measurable health standards for master and release branches, and coordinate inference-impacting rollout across multiple product and release projects.\n\n - Hands-on technical authority: Lead through code, test architecture, difficult debugging, quality metrics, and evidence-based release decisions.\n\n - Team multiplier: Raise the technical bar, mentor engineers, and align feature, infrastructure, integration, qualification, and release teams.\n\n\nWHAT YOU WILL DO\n\n - Define the Release Integration Testing strategy, engagement criteria, ownership boundaries, entry and exit criteria, coverage expectations, and escalation thresholds for AI Inference Core.\n\n - Engage early on high-risk inference changes; identify dependencies and interaction risks across runtime, host, device programming, memory, scheduling, model execution, infrastructure, and hardware.\n\n - Own the inference-path readiness gate by reviewing unit, simulation, benchmark, feature-test, and integration evidence, documenting gaps, and approving integration readiness before release entry.\n\n - Lead integrated inference E2E validation across features and the cloud-to-wafer stack; promote durable feature tests and add risk-based scenarios to release regression.\n\n - Improve master and release-branch stability through actionable health metrics, failure classification, release-quality reporting, dashboards, qualification workflows, and release pipelines.\n\n - Lead first-pass regression and rollout triage, coordinate owners through resolution, drive RCA, place missing coverage at the correct layer, and plan rollout across multiple product and release projects.\n\n - Partner with and mentor SDETs, feature teams, Integration, Core Infra, release owners, and deployment teams; between active engagements, advance automation efficiency, diagnostics, probes, and roadmap test planning.\n\n\nMINIMUM SKILLS & QUALIFICATIONS\n\n - Strong software-engineering fundamentals and programming ability in Python Go, or a similar language.\n\n - Demonstrated technical leadership in software quality, test infrastructure, systems validation, release engineering, or complex software integration.\n\n - Experience designing automation and test architecture for distributed, systems-level, infrastructure, or AI software.\n\n - Proven ability to break down ambiguous cross-stack failures, form hypotheses, gather evidence, and drive issues to resolution.\n\n - Strong understanding of risk-based testing, release readiness, regression strategy, failure analysis, and quality metrics.\n\n - Ability to influence and align multiple engineering teams without relying solely on organizational authority.\n\n - Clear communication and sound judgment during high-pressure release situations, including the ability to explain technical risk to engineering and leadership audiences.\n\n\nPREFERRED SKILLS\n\n - Experience with software/hardware co-design, hardware accelerators, compilers, kernels, runtimes, or low-level systems.\n\n - Experience with AI infrastructure, model deployment, LLMs, multimodal workloads, or large-scale compute clusters.\n\n - Experience building test frameworks, distributed test systems, release pipelines, dashboards, or internal developer tooling.\n\n - Experience with performance testing, profiling, observability, fault injection, reliability, or production failure analysis.\n\n - Experience in a startup or similarly fast-moving, resource-constrained engineering environment.\n\n - Track record of taking a quality or release capability from zero to one and scaling it across teams.\n\n - Familiarity with containers, cluster orchestration, cloud infrastructure, CI/CD, or high-performance computing.\n\n\nWHAT SUCCESS LOOKS LIKE\n\n - Release readiness is based on explicit criteria and high-signal evidence rather than intuition.\n\n - Fewer inference-path integration defects are first discovered in final release qualification or production.\n\n - Cross-component risks are found earlier, debug cycles are shorter, and coverage ownership is explicit.\n\n - Master and release-branch health is measurable, actionable, and steadily improving.\n\n - Test automation and release infrastructure shorten feedback loops without sacrificing signal quality.\n\n - Release metrics and reports drive clear decisions, ownership, and predictable feature rollout.\n\n - Engineers across the organization are more effective because Release Integration Testing provides strong technical direction, tooling, and mentorship.\n\n\nLOCATION\n\n - This role requires in-office presence, at least three days per week. Fully remote work is not available.\n\n - Office locations: Sunnyvale, CA or Toronto, ON.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"70f859f8-ea99-42bb-a2ac-ac0d230a2929","title":"AI Inference Core - Infrastructure SW Engineer","department":"Software Engineering ","team":"Inference Core","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2026-09-03T19:04:59.935+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressRegion":"California ","addressCountry":"United States","addressLocality":"Sunnyvale "}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/70f859f8-ea99-42bb-a2ac-ac0d230a2929","applyUrl":"https://jobs.ashbyhq.com/cerebras/70f859f8-ea99-42bb-a2ac-ac0d230a2929/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
The Core Infrastructure team builds the software systems that power engineering workflows across Cerebras.
Our infrastructure coordinates complex work across machines, clusters, development environments, and hardware systems. We build orchestration frameworks, execution engines, scheduling systems, test infrastructure, developer tools, and reusable software platforms that allow engineers to build, test, qualify, and deliver software reliably at scale.
These systems are primarily built in Python, but the work goes far beyond scripting or automation. Our frameworks act as the control plane for distributed workflows, managing resources, execution state, concurrency, failures, retries, dependencies, and observability across large and complex environments.
We are hiring a Software Engineer to design and build the core software behind Cerebras engineering infrastructure.
You will work on Python frameworks, orchestration systems, distributed execution, scheduling, test infrastructure, and developer tooling. You will help define the architecture and APIs that other engineering teams depend on every day.
This role is a strong fit for an engineer who enjoys reading unfamiliar code, understanding how systems fit together, debugging difficult problems, and improving the underlying design rather than applying one-off fixes.
We value strong software-engineering fundamentals, independent problem solving, and sound systems thinking more than familiarity with any particular infrastructure product.
Design, develop, test, and maintain Python frameworks and services used to orchestrate engineering workflows across machines and clusters.
Build reusable abstractions for scheduling, distributed execution, resource management, test execution, workflow planning, and failure recovery.
Define clear APIs, module boundaries, extension points, and data models that allow infrastructure systems to evolve without becoming difficult to maintain.
Reason about concurrency, asynchronous execution, multiprocessing, state management, retries, idempotency, cancellation, and partial failures.
Debug complex issues spanning Python applications, operating systems, processes, filesystems, networking, remote machines, and distributed services.
Write high-quality automated tests and documentation for infrastructure that is expected to be reliable and widely reused.
Partner with platform, CI, release, quality, ML systems, and product engineering teams to understand requirements and translate them into scalable software designs.
3+ years of professional software-engineering experience.
Strong proficiency in Python and a solid understanding of the language’s strengths, limitations, and runtime behavior.
Experience designing maintainable software systems, libraries, frameworks, backend services, or developer-facing APIs.
Good judgment around software architecture, abstraction boundaries, design patterns, extensibility, and long-term maintainability.
Understanding of concurrency concepts such as processes, threads, asynchronous execution, synchronization, and shared state.
Foundational understanding of operating systems, including processes, signals, filesystems, resource management, and program execution.
Foundational understanding of distributed-systems concepts such as retries, timeouts, idempotency, partial failure, coordination, and eventual consistency.
Strong debugging and problem-solving skills, including the ability to form hypotheses, gather evidence, and work through unfamiliar systems independently.
Experience with Python concurrency technologies such as asyncio, multiprocessing, concurrent futures, or event-driven systems.
Experience building orchestration engines, workflow systems, schedulers, distributed job runners, or control-plane software.
Experience developing test infrastructure or extensions for frameworks such as pytest.
Familiarity with CI systems, build systems, release infrastructure, or developer-productivity tooling.
Experience with Kubernetes, containerized environments, cluster schedulers, or remote execution systems.
BS/MS in Computer Science or a related field, or equivalent practical experience.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n\nABOUT THE TEAM\n\nThe Core Infrastructure team builds the software systems that power engineering workflows across Cerebras.\n\nOur infrastructure coordinates complex work across machines, clusters, development environments, and hardware systems. We build orchestration frameworks, execution engines, scheduling systems, test infrastructure, developer tools, and reusable software platforms that allow engineers to build, test, qualify, and deliver software reliably at scale.\n\nThese systems are primarily built in Python, but the work goes far beyond scripting or automation. Our frameworks act as the control plane for distributed workflows, managing resources, execution state, concurrency, failures, retries, dependencies, and observability across large and complex environments.\n\n\n\n\n\nABOUT THE ROLE\n\nWe are hiring a Software Engineer to design and build the core software behind Cerebras engineering infrastructure.\n\nYou will work on Python frameworks, orchestration systems, distributed execution, scheduling, test infrastructure, and developer tooling. You will help define the architecture and APIs that other engineering teams depend on every day.\n\nThis role is a strong fit for an engineer who enjoys reading unfamiliar code, understanding how systems fit together, debugging difficult problems, and improving the underlying design rather than applying one-off fixes.\n\nWe value strong software-engineering fundamentals, independent problem solving, and sound systems thinking more than familiarity with any particular infrastructure product.\n\n\n\n\nRESPONSIBILITIES\n\n - Design, develop, test, and maintain Python frameworks and services used to orchestrate engineering workflows across machines and clusters.\n\n - Build reusable abstractions for scheduling, distributed execution, resource management, test execution, workflow planning, and failure recovery.\n\n - Define clear APIs, module boundaries, extension points, and data models that allow infrastructure systems to evolve without becoming difficult to maintain.\n\n - Reason about concurrency, asynchronous execution, multiprocessing, state management, retries, idempotency, cancellation, and partial failures.\n\n - Debug complex issues spanning Python applications, operating systems, processes, filesystems, networking, remote machines, and distributed services.\n\n - Write high-quality automated tests and documentation for infrastructure that is expected to be reliable and widely reused.\n\n - Partner with platform, CI, release, quality, ML systems, and product engineering teams to understand requirements and translate them into scalable software designs.\n\n\nSKILLS & QUALIFICATIONS\n\n - 3+ years of professional software-engineering experience.\n\n - Strong proficiency in Python and a solid understanding of the language’s strengths, limitations, and runtime behavior.\n\n - Experience designing maintainable software systems, libraries, frameworks, backend services, or developer-facing APIs.\n\n - Good judgment around software architecture, abstraction boundaries, design patterns, extensibility, and long-term maintainability.\n\n - Understanding of concurrency concepts such as processes, threads, asynchronous execution, synchronization, and shared state.\n\n - Foundational understanding of operating systems, including processes, signals, filesystems, resource management, and program execution.\n\n - Foundational understanding of distributed-systems concepts such as retries, timeouts, idempotency, partial failure, coordination, and eventual consistency.\n\n - Strong debugging and problem-solving skills, including the ability to form hypotheses, gather evidence, and work through unfamiliar systems independently.\n\n\nPREFERRED SKILLS & QUALIFICATIONS\n\n - Experience with Python concurrency technologies such as asyncio, multiprocessing, concurrent futures, or event-driven systems.\n\n - Experience building orchestration engines, workflow systems, schedulers, distributed job runners, or control-plane software.\n\n - Experience developing test infrastructure or extensions for frameworks such as pytest.\n\n - Familiarity with CI systems, build systems, release infrastructure, or developer-productivity tooling.\n\n - Experience with Kubernetes, containerized environments, cluster schedulers, or remote execution systems.\n\n - BS/MS in Computer Science or a related field, or equivalent practical experience.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"b418fbca-9a33-4ac5-adb3-24dd57b1c678","title":"Staff Software Engineer, GPU Inference","department":"Software Engineering ","team":"Inference Service","employmentType":"FullTime","location":"Toronto, CAN","secondaryLocations":[{"location":"Sunnyvale, CA","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}}}],"publishedAt":"2026-07-28T15:19:52.049+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"postalCode":"M5H1Z5","addressRegion":"Ontario","streetAddress":"67 Richmond St W","addressCountry":"Canada","addressLocality":"Toronto"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/b418fbca-9a33-4ac5-adb3-24dd57b1c678","applyUrl":"https://jobs.ashbyhq.com/cerebras/b418fbca-9a33-4ac5-adb3-24dd57b1c678/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Cerebras is building a new generation of disaggregated AI inference systems that combine GPU-accelerated prefill with ultra-fast decode on the Cerebras Wafer-Scale Engine.
We are hiring a Software Engineer to productionize and optimize our GPU serving stack, working across our custom inference APIs, the vLLM serving runtime, the AMD ROCm software stack, and rack-scale AMD GPU infrastructure, to make this new serving path reliable, numerically correct, observable, and exceptionally performant.
You will write production code, establish operational practices for a new accelerator fleet, and drive improvements in time to first token, throughput, tail latency, and capacity efficiency. This is a hands-on role requiring deep debugging and optimization across application, runtime, distributed systems, and hardware layers.
Productionize the GPU inference stack. Design, build, deploy, and maintain the complete GPU prefill path, spanning API services, model-serving workers, vLLM, PyTorch, ROCm, GPU nodes, networking, and rack-scale infrastructure.
Own GPU operational readiness. Establish deployment, upgrade, rollback, health-checking, capacity-management, and failure-recovery practices for the AMD GPU fleet. Build automation that makes driver, firmware, runtime, model, and container compatibility explicit and reproducible.
Drive reliability in production. Define service-level indicators and objectives for GPU-backed inference. Improve fault isolation, graceful degradation, automated recovery, incident response, and post-incident remediation across the serving stack.
Improve inference performance. Profile and optimize time to first token, request throughput, tokens per second per GPU, tail latency, GPU utilization, memory efficiency, and rack-level capacity under representative production workloads.
Optimize model-serving behavior. Tune and improve scheduling, continuous batching, prefix caching, KV-cache management, tensor and expert parallelism, request admission, quantization, graph execution, and distributed communication.
Debug across system layers. Diagnose complex failures and performance regressions across application code, vLLM, PyTorch, ROCm/HIP, collective communication libraries, kernels, drivers, firmware, networking, and hardware.
Ensure numerical correctness. Build validation and regression infrastructure for model quality, numerical accuracy, precision changes, quantization, determinism, and compatibility across software and hardware releases.
Build performance and correctness infrastructure. Develop representative benchmarks, workload replay tools, profiling automation, release qualification, dashboards, and regression gates. Turn one-off investigations into repeatable engineering systems.
8+ years of software engineering experience, including substantial individual-contributor ownership of complex production systems.
Experience building, operating, or optimizing production inference systems for large language models, multimodal models, or similarly demanding GPU workloads.
Strong programming ability in C++ and Python, including experience with multithreading, concurrency, memory management, and performance-sensitive software.
Hands-on experience with a high-performance model-serving framework such as vLLM, SGLang, TensorRT-LLM, Triton Inference Server, or an equivalent internally developed system.
Strong understanding of GPU execution and performance, including asynchronous execution, memory movement, synchronization, kernel launches, communication overhead, and profiling methodology.
Experience debugging distributed systems across multiple layers rather than treating the serving framework or accelerator runtime as a black box.
Experience with Linux, containers, Kubernetes or comparable orchestration systems, observability, CI/CD, and operating latency-sensitive services in production.
Ability to design rigorous benchmarks, interpret noisy performance results, identify bottlenecks, and translate findings into production improvements.
Strong communication and technical leadership skills, with a demonstrated ability to drive ambiguous cross-functional projects to completion.
Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or a related discipline, or equivalent practical experience.
Experience with AMD Instinct accelerators and the ROCm ecosystem, including HIP, RCCL, rocprofiler, AMD SMI, AITER, hipBLASLt, Composable Kernel, or related libraries and tools.
Deep CUDA experience that demonstrates an ability to transfer GPU systems knowledge across accelerator platforms.
Experience modifying or contributing to vLLM, SGLang, PyTorch, Triton, TensorRT-LLM, or another open-source ML systems project.
Experience optimizing prefill-heavy or disaggregated prefill/decode inference architectures.
Understanding of KV-cache transfer, prefix caching, continuous batching, chunked prefill, request scheduling, and memory-aware admission control.
Experience with multi-GPU and multi-node inference, including tensor parallelism, pipeline parallelism, expert parallelism, RDMA, collective communication, and failure handling.
Experience optimizing Mixture-of-Experts or multimodal models.
Knowledge of GPU kernel optimization, operator fusion, graph capture, attention kernels, GEMM tuning, and communication/computation overlap.
Experience with reduced-precision inference and quantization formats such as BF16, FP8, FP4, INT8, or INT4, including validation of their numerical and model-quality effects.
Experience building numerical-comparison, determinism, model-validation, or performance-regression test systems.
Experience collaborating directly with accelerator vendors, framework maintainers, or open-source communities.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n\nABOUT THE ROLE\n\nCerebras is building a new generation of disaggregated AI inference systems https://www.cerebras.ai/press-release/amd-and-cerebras-announce-industry-leading-ultra-low-latency-and-high-throughput-ai-inference that combine GPU-accelerated prefill with ultra-fast decode on the Cerebras Wafer-Scale Engine.\n\nWe are hiring a Software Engineer to productionize and optimize our GPU serving stack, working across our custom inference APIs, the vLLM serving runtime, the AMD ROCm software stack, and rack-scale AMD GPU infrastructure, to make this new serving path reliable, numerically correct, observable, and exceptionally performant.\n\nYou will write production code, establish operational practices for a new accelerator fleet, and drive improvements in time to first token, throughput, tail latency, and capacity efficiency. This is a hands-on role requiring deep debugging and optimization across application, runtime, distributed systems, and hardware layers.\n\n\nRESPONSIBILITIES\n\n - Productionize the GPU inference stack. Design, build, deploy, and maintain the complete GPU prefill path, spanning API services, model-serving workers, vLLM, PyTorch, ROCm, GPU nodes, networking, and rack-scale infrastructure.\n\n - Own GPU operational readiness. Establish deployment, upgrade, rollback, health-checking, capacity-management, and failure-recovery practices for the AMD GPU fleet. Build automation that makes driver, firmware, runtime, model, and container compatibility explicit and reproducible.\n\n - Drive reliability in production. Define service-level indicators and objectives for GPU-backed inference. Improve fault isolation, graceful degradation, automated recovery, incident response, and post-incident remediation across the serving stack.\n\n - Improve inference performance. Profile and optimize time to first token, request throughput, tokens per second per GPU, tail latency, GPU utilization, memory efficiency, and rack-level capacity under representative production workloads.\n\n - Optimize model-serving behavior. Tune and improve scheduling, continuous batching, prefix caching, KV-cache management, tensor and expert parallelism, request admission, quantization, graph execution, and distributed communication.\n\n - Debug across system layers. Diagnose complex failures and performance regressions across application code, vLLM, PyTorch, ROCm/HIP, collective communication libraries, kernels, drivers, firmware, networking, and hardware.\n\n - Ensure numerical correctness. Build validation and regression infrastructure for model quality, numerical accuracy, precision changes, quantization, determinism, and compatibility across software and hardware releases.\n\n - Build performance and correctness infrastructure. Develop representative benchmarks, workload replay tools, profiling automation, release qualification, dashboards, and regression gates. Turn one-off investigations into repeatable engineering systems.\n\n\nMINIMUM QUALIFICATIONS\n\n - 8+ years of software engineering experience, including substantial individual-contributor ownership of complex production systems.\n\n - Experience building, operating, or optimizing production inference systems for large language models, multimodal models, or similarly demanding GPU workloads.\n\n - Strong programming ability in C++ and Python, including experience with multithreading, concurrency, memory management, and performance-sensitive software.\n\n - Hands-on experience with a high-performance model-serving framework such as vLLM, SGLang, TensorRT-LLM, Triton Inference Server, or an equivalent internally developed system.\n\n - Strong understanding of GPU execution and performance, including asynchronous execution, memory movement, synchronization, kernel launches, communication overhead, and profiling methodology.\n\n - Experience debugging distributed systems across multiple layers rather than treating the serving framework or accelerator runtime as a black box.\n\n - Experience with Linux, containers, Kubernetes or comparable orchestration systems, observability, CI/CD, and operating latency-sensitive services in production.\n\n - Ability to design rigorous benchmarks, interpret noisy performance results, identify bottlenecks, and translate findings into production improvements.\n\n - Strong communication and technical leadership skills, with a demonstrated ability to drive ambiguous cross-functional projects to completion.\n\n - Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or a related discipline, or equivalent practical experience.\n\n\nPREFERRED QUALIFICATIONS\n\n - Experience with AMD Instinct accelerators and the ROCm ecosystem, including HIP, RCCL, rocprofiler, AMD SMI, AITER, hipBLASLt, Composable Kernel, or related libraries and tools.\n\n - Deep CUDA experience that demonstrates an ability to transfer GPU systems knowledge across accelerator platforms.\n\n - Experience modifying or contributing to vLLM, SGLang, PyTorch, Triton, TensorRT-LLM, or another open-source ML systems project.\n\n - Experience optimizing prefill-heavy or disaggregated prefill/decode inference architectures.\n\n - Understanding of KV-cache transfer, prefix caching, continuous batching, chunked prefill, request scheduling, and memory-aware admission control.\n\n - Experience with multi-GPU and multi-node inference, including tensor parallelism, pipeline parallelism, expert parallelism, RDMA, collective communication, and failure handling.\n\n - Experience optimizing Mixture-of-Experts or multimodal models.\n\n - Knowledge of GPU kernel optimization, operator fusion, graph capture, attention kernels, GEMM tuning, and communication/computation overlap.\n\n - Experience with reduced-precision inference and quantization formats such as BF16, FP8, FP4, INT8, or INT4, including validation of their numerical and model-quality effects.\n\n - Experience building numerical-comparison, determinism, model-validation, or performance-regression test systems.\n\n - Experience collaborating directly with accelerator vendors, framework maintainers, or open-source communities.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"c5c87a44-f891-4842-955f-f1bb59d9d124","title":"Senior Quality Assurance Engineer","department":"Software Engineering ","team":"Inference Service","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2026-07-28T00:35:29.692+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/c5c87a44-f891-4842-955f-f1bb59d9d124","applyUrl":"https://jobs.ashbyhq.com/cerebras/c5c87a44-f891-4842-955f-f1bb59d9d124/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Cerebras Systems Inc. has multiple openings for Senior Quality Assurance Engineer
Title: Senior Quality Assurance Engineer
Job Duties:
Design and develop automated test frameworks and execute software validation using Python, Java, and Selenium to ensure quality and reliability of cloud-based inference services.
Design, implement, and execute functional, integration, regression, and performance test strategies for AI/ML systems using Python, REST APIs and automation tools within CI/CD pipelines.
Develop and maintain automated test scripts and frameworks using Selenium, Java, and Python integrated with Jenkins and cloud environments such as AWS and Kubernetes to validate scalable SaaS deployments.
Perform system, API, and data validation testing using SQL, Oracle/RDBMS, and REST API tools to ensure data integrity, transformation accuracy, and end-to-end pipeline reliability.
Monitor system performance, latency, and model behavior using tools such as JMeter and observability platforms: analyze results to ensure optimal performance of distributed AI systems.
Triage defects, perform root cause analysis, and debug complex issues across distributed cloud systems and AI inference infrastructure using logs, monitoring tools, and engineering best practices.
Document test plans, test cases, results, and defects. Track issues using Jira or Rally and collaborate with cross-functional teams to ensure high-quality product releases.
Minimum Requirements:
Master’s degree or foreign equivalent degree in Computer Engineering, Computer Science, or a related field and 4 years of experience as Quality Engineer, Software QA Engineer, Sr. Software QA Engineer, Senior Quality Assurance Engineer or a related occupation required.
Required Skills:
Java and QE Automation;
Selenium testing with Page Object Model-based frameworks;
Visual Studio Code;
Rally;
REST API Testing;
AWS, Jenkins, and CI/CD pipeline;
SQL;
JIRA; and
JMeter
Additional Information:
Employer’s name: Cerebras Systems Inc.
Job site : 1237 E Arques Avenue, Sunnyvale, CA 94085
Telecommuting permitted
Salary Range: $220,000.00 per year to $240,000.00 per year
If you are interested in applying for this position, please apply online on this web page or mail resume to HR at Cerebras Systems Inc., 1237 E Arques Avenue, Sunnyvale, CA 94085. Please reference Job # 149 on resume or cover letter.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n\n\nCerebras Systems Inc. has multiple openings for Senior Quality Assurance Engineer\n\n \n\nTitle: Senior Quality Assurance Engineer\n\n\n\nJob Duties:\n\n - Design and develop automated test frameworks and execute software validation using Python, Java, and Selenium to ensure quality and reliability of cloud-based inference services.\n\n - Design, implement, and execute functional, integration, regression, and performance test strategies for AI/ML systems using Python, REST APIs and automation tools within CI/CD pipelines.\n\n - Develop and maintain automated test scripts and frameworks using Selenium, Java, and Python integrated with Jenkins and cloud environments such as AWS and Kubernetes to validate scalable SaaS deployments.\n\n - Perform system, API, and data validation testing using SQL, Oracle/RDBMS, and REST API tools to ensure data integrity, transformation accuracy, and end-to-end pipeline reliability.\n\n - Monitor system performance, latency, and model behavior using tools such as JMeter and observability platforms: analyze results to ensure optimal performance of distributed AI systems.\n\n - Triage defects, perform root cause analysis, and debug complex issues across distributed cloud systems and AI inference infrastructure using logs, monitoring tools, and engineering best practices.\n\n - Document test plans, test cases, results, and defects. Track issues using Jira or Rally and collaborate with cross-functional teams to ensure high-quality product releases.\n\n\n\nMinimum Requirements:\n\n \n\nMaster’s degree or foreign equivalent degree in Computer Engineering, Computer Science, or a related field and 4 years of experience as Quality Engineer, Software QA Engineer, Sr. Software QA Engineer, Senior Quality Assurance Engineer or a related occupation required.\n\n \n\nRequired Skills:\n\n \n\n - Java and QE Automation;\n\n - Selenium testing with Page Object Model-based frameworks;\n\n - Visual Studio Code;\n\n - Rally;\n\n - REST API Testing;\n\n - AWS, Jenkins, and CI/CD pipeline;\n\n - SQL;\n\n - JIRA; and\n\n - JMeter\n\n\n\nAdditional Information:\n\nEmployer’s name: Cerebras Systems Inc.\n\nJob site : 1237 E Arques Avenue, Sunnyvale, CA 94085\n\nTelecommuting permitted\n\nSalary Range: $220,000.00 per year to $240,000.00 per year\n\nIf you are interested in applying for this position, please apply online on this web page or mail resume to HR at Cerebras Systems Inc., 1237 E Arques Avenue, Sunnyvale, CA 94085. Please reference Job # 149 on resume or cover letter.\n\n\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"22332143-b54d-47f2-944e-2fc52d5446df","title":"Hardware Analytics Engineer","department":"Hardware","team":"Systems","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2026-07-28T00:54:53.401+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressRegion":"California ","addressCountry":"United States","addressLocality":"Sunnyvale "}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/22332143-b54d-47f2-944e-2fc52d5446df","applyUrl":"https://jobs.ashbyhq.com/cerebras/22332143-b54d-47f2-944e-2fc52d5446df/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Cerebras Systems Inc. has multiple openings for Hardware Analytics Engineer
Title: Hardware Analytics Engineer
Job Duties:
Design and optimize scalable data pipeline architectures for multi-terabyte hardware telemetry, reliability analytics, and performance optimization.
Architect, develop, and optimize hyperscale data pipeline frameworks and ETL processes to aggregate, process, and analyze multi-terabyte hardware performance and telemetry streams, including utilization, power, thermal, acoustic, and reliability metrics across heterogeneous compute, storage, and AI server platforms, ensuring hardware performance compliance and operational reliability.
Design and implement hardware performance analysis and anomaly detection systems using Python, SQL, Tableau, Hive, and Spark to forecast hardware failure curves, identify performance bottlenecks, and generate prescriptive recommendations for hardware and system optimization.
Lead hardware characterization experiments and thermal/cooling A/B studies to evaluate operational envelopes, delivering validated strategies that reduce carbon footprint, improve water usage efficiency, and maintain or enhance system reliability.
Engineer telemetry ingestion, monitoring, and visualization systems to provide real-time, high-fidelity hardware health data to hardware, firmware, and datacenter operations teams, enabling data-driven decision-making at scale.
Define, operationalize, and maintain custom efficiency and reliability metrics; perform root cause analysis of systemic failures using large-scale statistical and machine learning methods; and deploy solutions that improve platform scalability, energy efficiency, and sustainability.
Collaborate with cross-functional engineering teams to troubleshoot complex failures, isolate defective components, and implement systemic fixes across CPU, GPU, DRAM, PCIe, networking, and storage subsystems.
Support the evolution and optimization of next-generation AI platforms and silicon products, including hardware subsystems (CPU, GPU, DRAM, PCIe, networking, and storage), to meet the performance, scalability, and efficiency demands of large language model training and inference workloads.
Minimum Requirements:
Master’s degree or foreign equivalent degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field and 3 years of experience as Hardware Analytics Engineer, Hardware Engineer, Data Engineer, or a related occupation required.
Required Skills:
Large-scale data pipeline architecture and ETL, distributed data processing (Hive, Spark), and dashboard development;
Python, SQL, Tableau, Linux, and automation scripting;
Design, training, and deployment of machine learning models for hardware performance optimization and failure prediction;
Predictive modeling, statistical analysis, A/B testing, anomaly detection, and data visualization in hardware reliability and performance; and
Hardware analytics for compute, storage, and AI servers; power and thermal optimization; GPU burn-in efficiency optimization; and reliability modeling for AI hardware systems and components including CPU, GPU, DRAM, and SSD.
Additional Information:
Employer’s name: Cerebras Systems Inc.
Job site : 1237 E Arques Avenue, Sunnyvale, CA 94085
Telecommuting permitted
Salary Range: $213,675.00 per year to $225,000.00 per year
If you are interested in applying for this position, please apply online on this web page or mail resume to HR at Cerebras Systems Inc., 1237 E Arques Avenue, Sunnyvale, CA 94085. Please reference Job # 144 on resume or cover letter.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n\n\nCerebras Systems Inc. has multiple openings for Hardware Analytics Engineer\n\n\n\nTitle: Hardware Analytics Engineer\n\n\n\nJob Duties:\n\n - Design and optimize scalable data pipeline architectures for multi-terabyte hardware telemetry, reliability analytics, and performance optimization.\n\n - Architect, develop, and optimize hyperscale data pipeline frameworks and ETL processes to aggregate, process, and analyze multi-terabyte hardware performance and telemetry streams, including utilization, power, thermal, acoustic, and reliability metrics across heterogeneous compute, storage, and AI server platforms, ensuring hardware performance compliance and operational reliability.\n\n - Design and implement hardware performance analysis and anomaly detection systems using Python, SQL, Tableau, Hive, and Spark to forecast hardware failure curves, identify performance bottlenecks, and generate prescriptive recommendations for hardware and system optimization.\n\n - Lead hardware characterization experiments and thermal/cooling A/B studies to evaluate operational envelopes, delivering validated strategies that reduce carbon footprint, improve water usage efficiency, and maintain or enhance system reliability.\n\n - Engineer telemetry ingestion, monitoring, and visualization systems to provide real-time, high-fidelity hardware health data to hardware, firmware, and datacenter operations teams, enabling data-driven decision-making at scale.\n\n - Define, operationalize, and maintain custom efficiency and reliability metrics; perform root cause analysis of systemic failures using large-scale statistical and machine learning methods; and deploy solutions that improve platform scalability, energy efficiency, and sustainability.\n\n - Collaborate with cross-functional engineering teams to troubleshoot complex failures, isolate defective components, and implement systemic fixes across CPU, GPU, DRAM, PCIe, networking, and storage subsystems.\n\n - Support the evolution and optimization of next-generation AI platforms and silicon products, including hardware subsystems (CPU, GPU, DRAM, PCIe, networking, and storage), to meet the performance, scalability, and efficiency demands of large language model training and inference workloads.\n \n \n\nMinimum Requirements:\n\nMaster’s degree or foreign equivalent degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field and 3 years of experience as Hardware Analytics Engineer, Hardware Engineer, Data Engineer, or a related occupation required.\n\n\n\nRequired Skills:\n\n - Large-scale data pipeline architecture and ETL, distributed data processing (Hive, Spark), and dashboard development;\n\n - Python, SQL, Tableau, Linux, and automation scripting;\n\n - Design, training, and deployment of machine learning models for hardware performance optimization and failure prediction;\n\n - Predictive modeling, statistical analysis, A/B testing, anomaly detection, and data visualization in hardware reliability and performance; and\n\n - Hardware analytics for compute, storage, and AI servers; power and thermal optimization; GPU burn-in efficiency optimization; and reliability modeling for AI hardware systems and components including CPU, GPU, DRAM, and SSD.\n\n \n\nAdditional Information:\n\nEmployer’s name: Cerebras Systems Inc.\n\nJob site : 1237 E Arques Avenue, Sunnyvale, CA 94085\n\nTelecommuting permitted\n\nSalary Range: $213,675.00 per year to $225,000.00 per year\n\nIf you are interested in applying for this position, please apply online on this web page or mail resume to HR at Cerebras Systems Inc., 1237 E Arques Avenue, Sunnyvale, CA 94085. Please reference Job # 144 on resume or cover letter.\n\n\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"31def8de-acc5-4db3-9020-1fdfa8e783da","title":"Systems Debug Engineer- EE","department":"Hardware","team":"Quality & Reliability","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2026-07-29T19:16:21.395+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressRegion":"California ","addressCountry":"United States","addressLocality":"Sunnyvale "}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/31def8de-acc5-4db3-9020-1fdfa8e783da","applyUrl":"https://jobs.ashbyhq.com/cerebras/31def8de-acc5-4db3-9020-1fdfa8e783da/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Role Summary
Bringing the world’s largest and most complex compute systems from design to production—and maintaining them in the field—demands deep integration and debugging expertise across electrical, thermal, and mechanical domains.
We are looking for a versatile Electrical Engineer who thrives at the bench—diagnosing complex, multi-domain failures and driving root cause to the silicon, PCB, component, or system level, and feeding those learnings back into the next generation of Cerebras hardware. The role also includes remotely diagnosing deployed systems using Linux tools, logs, and telemetry to guide recovery and service decisions.
This role is ideal for a curious, self-directed engineer who enjoys owning complex problems from initial failure detection through root cause and corrective action.
Responsibilities
Characterize failure signatures and perform hands-on troubleshooting at the system, board, and component level.
Drive failure analysis to root cause—down to silicon, PCB, or external components—using structured, first-principles problem solving.
Remotely diagnose failures in deployed systems using Linux command-line tools, system logs, telemetry, diagnostic utilities, and remote-access workflows.
Analyze and document results clearly, and provide actionable recommendations to design and manufacturing teams.
Interface across internal groups (ASIC, systems, and manufacturing) and with external vendors to resolve issues and close corrective actions.
Participate in design reviews for next-generation systems, contributing recommendations spanning electrical design-for-test (DFT), mechanical, and thermal improvements.
Skills & Qualifications
Required:
Bachelor’s degree in Electrical Engineering or a related field.
3-5+ years of experience in hardware bring-up, system integration, board/system debug, or failure analysis.
Strong analytical, diagnostic, and problem-solving skills, grounded in first principles.
Strong drive to self-educate and operate with autonomy in fast-moving, ambiguous environments.
Hands-on experience with oscilloscopes and standard electrical bench instrumentation.
Scripting experience, preferably Python, for data analysis and automation.
Excellent communication skills, with the ability to distill complex technical findings into clear, concise insights.
Preferred:
Comfort working in Linux environments and using command-line interfaces to inspect logs, query system state, run diagnostics, and troubleshoot compute hardware.
Experience with failure analysis (FA) techniques such as cross-section, SEM, and X-ray.
Experience working with Contract Manufacturers and implementing process and design level changes.
Experience reading electrical schematics and board layouts.
Familiarity with PCB design and assembly processes (e.g., PCB surface finishes, convection reflow, and solder properties).
Understanding of thermal, electrical, and mechanical interactions in high-performance systems
Location: Sunnyvale, CA
The base salary range for this position is $190,000 to $230,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nRole Summary\n\nBringing the world’s largest and most complex compute systems from design to production—and maintaining them in the field—demands deep integration and debugging expertise across electrical, thermal, and mechanical domains.\n\nWe are looking for a versatile Electrical Engineer who thrives at the bench—diagnosing complex, multi-domain failures and driving root cause to the silicon, PCB, component, or system level, and feeding those learnings back into the next generation of Cerebras hardware. The role also includes remotely diagnosing deployed systems using Linux tools, logs, and telemetry to guide recovery and service decisions.\n\nThis role is ideal for a curious, self-directed engineer who enjoys owning complex problems from initial failure detection through root cause and corrective action.\n\nResponsibilities\n\n - Characterize failure signatures and perform hands-on troubleshooting at the system, board, and component level.\n\n - Drive failure analysis to root cause—down to silicon, PCB, or external components—using structured, first-principles problem solving.\n\n - Remotely diagnose failures in deployed systems using Linux command-line tools, system logs, telemetry, diagnostic utilities, and remote-access workflows.\n\n - Analyze and document results clearly, and provide actionable recommendations to design and manufacturing teams.\n\n - Interface across internal groups (ASIC, systems, and manufacturing) and with external vendors to resolve issues and close corrective actions.\n\n - Participate in design reviews for next-generation systems, contributing recommendations spanning electrical design-for-test (DFT), mechanical, and thermal improvements.\n\nSkills & Qualifications\n\nRequired:\n\n - Bachelor’s degree in Electrical Engineering or a related field.\n\n - 3-5+ years of experience in hardware bring-up, system integration, board/system debug, or failure analysis.\n\n - Strong analytical, diagnostic, and problem-solving skills, grounded in first principles.\n\n - Strong drive to self-educate and operate with autonomy in fast-moving, ambiguous environments.\n\n - Hands-on experience with oscilloscopes and standard electrical bench instrumentation.\n\n - Scripting experience, preferably Python, for data analysis and automation.\n\n - Excellent communication skills, with the ability to distill complex technical findings into clear, concise insights.\n\nPreferred:\n\n - Comfort working in Linux environments and using command-line interfaces to inspect logs, query system state, run diagnostics, and troubleshoot compute hardware.\n\n - Experience with failure analysis (FA) techniques such as cross-section, SEM, and X-ray.\n\n - Experience working with Contract Manufacturers and implementing process and design level changes.\n\n - Experience reading electrical schematics and board layouts.\n\n - Familiarity with PCB design and assembly processes (e.g., PCB surface finishes, convection reflow, and solder properties).\n\n - Understanding of thermal, electrical, and mechanical interactions in high-performance systems\n\nLocation: Sunnyvale, CA\n\nThe base salary range for this position is $190,000 to $230,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"f25b9677-32fa-41ed-84d1-0ed704a98533","title":"Cluster Operations Software Engineer","department":"Software Engineering ","team":"Software Engineering ","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[{"location":"Toronto, CAN","address":{"postalAddress":{"addressRegion":"Ontario ","addressCountry":"Canada","addressLocality":"Toronto "}}},{"location":"Bengaluru, IND","address":{"postalAddress":{"addressRegion":"Karnataka ","addressCountry":"India","addressLocality":"Bengaluru"}}}],"publishedAt":"2026-08-13T16:10:31.749+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/f25b9677-32fa-41ed-84d1-0ed704a98533","applyUrl":"https://jobs.ashbyhq.com/cerebras/f25b9677-32fa-41ed-84d1-0ed704a98533/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
We are seeking a highly skilled and experienced AI Cluster Operations Engineer to manage and operate our cutting-edge machine learning compute clusters. These clusters would provide the candidate with an opportunity to work with the world's largest computer chip, the Wafer-Scale Engine (WSE), and the systems that harness its unparalleled power.
You will play a critical role in ensuring the health, performance, and availability of our infrastructure, maximizing compute capacity, and supporting our growing AI initiatives. This role requires a deep understanding of Linux-based systems, containerization technologies, and experience with monitoring and troubleshooting complex distributed systems. The ideal candidate is a proactive problem-solver with expertise in large-scale compute infrastructure, dependable and an advocate for customer success.
Deploy, configure, and debug container-based services using Docker.
Build and own software solutions that power cluster operations, including monitoring platforms, workflow automation systems, operational dashboards, and reliability tooling.
Collaborate with cross-functional teams to translate operational requirements into scalable O&M products and platform capabilities.
Develop APIs, automation services, and integrations that improve operational visibility, incident response, and fleet management across global AI infrastructure.
Manage and operate multiple advanced AI compute infrastructure clusters.
Monitor and oversee cluster health, proactively identifying and resolving potential issues.
Maximize compute capacity through optimization and efficient resource allocation.
Provide 24/7 monitoring and support, leveraging automated tools and performing hands-on troubleshooting as needed.
Handle engineering escalations and collaborate with other teams to resolve complex technical challenges.
Stay up-to-date with the latest advancements in AI compute infrastructure and related technologies.
6-8 years of relevant experience in managing and operating complex compute infrastructure, preferably in the context of machine learning or high-performance computing.
Proficient in Python and Go, with experience building operational platforms, workflow automation systems, and reliability tooling for large-scale infrastructure environments.
Experience and Expertise in distributed systems is a must.
Deep understanding of Linux-based compute systems and command-line tools.
Extensive knowledge of Docker containers and container orchestration platforms like k8s.
Proven ability to troubleshoot and resolve complex technical issues in a timely and efficient manner.
Experience with monitoring and alerting systems.
Should have a proven track record to own and drive challenges to completion.
Excellent communication and collaboration skills.
Ability to work effectively in a fast-paced environment.
Willingness to participate in a 24/7 on-call rotation.
Operating and Managing large scale AI clusters.
Knowledge of technologies like Ethernet, RoCE, TCP/IP, etc. is desired.
Knowledge of cloud computing platforms (e.g., AWS, GCP, Azure).
SF Bay Area.
Toronto, Canada.
Bangalore, India.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n\n\n\nTHE ROLE\n\n\n\nWe are seeking a highly skilled and experienced AI Cluster Operations Engineer to manage and operate our cutting-edge machine learning compute clusters. These clusters would provide the candidate with an opportunity to work with the world's largest computer chip, the Wafer-Scale Engine (WSE), and the systems that harness its unparalleled power.\n\n\n\nYou will play a critical role in ensuring the health, performance, and availability of our infrastructure, maximizing compute capacity, and supporting our growing AI initiatives. This role requires a deep understanding of Linux-based systems, containerization technologies, and experience with monitoring and troubleshooting complex distributed systems. The ideal candidate is a proactive problem-solver with expertise in large-scale compute infrastructure, dependable and an advocate for customer success.\n\n\n\n\nRESPONSIBILITIES\n\n - Deploy, configure, and debug container-based services using Docker.\n\n - Build and own software solutions that power cluster operations, including monitoring platforms, workflow automation systems, operational dashboards, and reliability tooling.\n\n - Collaborate with cross-functional teams to translate operational requirements into scalable O&M products and platform capabilities.\n\n - Develop APIs, automation services, and integrations that improve operational visibility, incident response, and fleet management across global AI infrastructure.\n\n - Manage and operate multiple advanced AI compute infrastructure clusters.\n\n - Monitor and oversee cluster health, proactively identifying and resolving potential issues.\n\n - Maximize compute capacity through optimization and efficient resource allocation.\n\n - Provide 24/7 monitoring and support, leveraging automated tools and performing hands-on troubleshooting as needed.\n\n - Handle engineering escalations and collaborate with other teams to resolve complex technical challenges.\n\n - Stay up-to-date with the latest advancements in AI compute infrastructure and related technologies.\n \n \n\n\nSKILLS AND REQUIREMENTS\n\n - 6-8 years of relevant experience in managing and operating complex compute infrastructure, preferably in the context of machine learning or high-performance computing.\n\n - Proficient in Python and Go, with experience building operational platforms, workflow automation systems, and reliability tooling for large-scale infrastructure environments.\n\n - Experience and Expertise in distributed systems is a must.\n\n - Deep understanding of Linux-based compute systems and command-line tools.\n\n - Extensive knowledge of Docker containers and container orchestration platforms like k8s.\n\n - Proven ability to troubleshoot and resolve complex technical issues in a timely and efficient manner.\n\n - Experience with monitoring and alerting systems.\n\n - Should have a proven track record to own and drive challenges to completion.\n\n - Excellent communication and collaboration skills.\n\n - Ability to work effectively in a fast-paced environment.\n\n - Willingness to participate in a 24/7 on-call rotation.\n \n \n\n\nPREFERRED SKILLS AND REQUIREMENTS\n\n - Operating and Managing large scale AI clusters.\n\n - Knowledge of technologies like Ethernet, RoCE, TCP/IP, etc. is desired.\n\n - Knowledge of cloud computing platforms (e.g., AWS, GCP, Azure).\n \n \n\n\nLOCATION\n\n - SF Bay Area.\n\n - Toronto, Canada.\n\n - Bangalore, India.\n\n\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"992de642-1400-4d21-825e-889876ae4d25","title":"Staff Design Verification Engineer","department":"Hardware","team":"Silicon","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2026-08-12T19:16:56.384+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/992de642-1400-4d21-825e-889876ae4d25","applyUrl":"https://jobs.ashbyhq.com/cerebras/992de642-1400-4d21-825e-889876ae4d25/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Key Responsibilities
Work with architects, designers, post silicon and software engineers to ensure a high-quality design that works first silicon.
Develop and implement verification strategies, detailed tests and coverage plans based on micro-architecture.
Create verification methodologies and reusable environments, including components such as stimulus, checkers, assertions, and coverage.
Implement tests, manage regressions, gather coverage, and debug test failures.
Collaborate with cross-functional teams including architecture, RTL design, physical design, firmware, and validation.
Analyze and debug complex issues across simulation, emulation, and silicon bring-up phases.
Continuously enhances verification infrastructure and flows to improve efficiency and quality.
Contribute to the evolution of the overall verification methodology and best practices across the organization.
Skills and Qualifications
Great debugging and problem-solving skills.
Deep knowledge of SystemVerilog testbench, DPI and UVM.
Excellent programming skills and knowledge of software engineering practices including object-oriented design.
Experience developing scalable and portable testbenches and components.
Experience with verification methodologies and tools such as simulators, waveform viewers, build and run automation, coverage collection, and gate level simulations.
Proficient in scripting languages such as Python or Perl.
Good interpersonal skills and the ability to work as a standout colleague are a must.
Extremely self-motivated and eager to solve problems
10+ years of Design Verification experience.
Desired Skills and Qualifications
Knowledge of pipelined processor architecture.
BS or MS in Computer Science or Electrical Engineering.
10+ years of hands-on Design Verification experience.
Location: Sunnyvale, CA
The base salary range for this position is $225,000 to $270,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nKey Responsibilities\n\n - Work with architects, designers, post silicon and software engineers to ensure a high-quality design that works first silicon.\n\n - Develop and implement verification strategies, detailed tests and coverage plans based on micro-architecture.\n\n - Create verification methodologies and reusable environments, including components such as stimulus, checkers, assertions, and coverage.\n\n - Implement tests, manage regressions, gather coverage, and debug test failures.\n\n - Collaborate with cross-functional teams including architecture, RTL design, physical design, firmware, and validation.\n\n - Analyze and debug complex issues across simulation, emulation, and silicon bring-up phases.\n\n - Continuously enhances verification infrastructure and flows to improve efficiency and quality.\n\n - Contribute to the evolution of the overall verification methodology and best practices across the organization.\n\nSkills and Qualifications\n\n - Great debugging and problem-solving skills.\n\n - Deep knowledge of SystemVerilog testbench, DPI and UVM.\n\n - Excellent programming skills and knowledge of software engineering practices including object-oriented design.\n\n - Experience developing scalable and portable testbenches and components.\n\n - Experience with verification methodologies and tools such as simulators, waveform viewers, build and run automation, coverage collection, and gate level simulations.\n\n - Proficient in scripting languages such as Python or Perl.\n\n - Good interpersonal skills and the ability to work as a standout colleague are a must.\n\n - Extremely self-motivated and eager to solve problems\n\n - 10+ years of Design Verification experience.\n\nDesired Skills and Qualifications\n\n - Knowledge of pipelined processor architecture.\n\n - BS or MS in Computer Science or Electrical Engineering.\n\n - 10+ years of hands-on Design Verification experience.\n\nLocation: Sunnyvale, CA\n\nThe base salary range for this position is $225,000 to $270,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.\n\n \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"7571d94f-66a6-4c43-88e2-55340f3b9383","title":"Inventory Control Analyst ","department":"Hardware","team":"Supply Chain","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2026-08-15T01:04:44.861+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressRegion":"California ","addressCountry":"United States","addressLocality":"Sunnyvale "}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/7571d94f-66a6-4c43-88e2-55340f3b9383","applyUrl":"https://jobs.ashbyhq.com/cerebras/7571d94f-66a6-4c43-88e2-55340f3b9383/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Position Summary
The Inventory Analyst is responsible for using data, reporting, and operational analysis to improve inventory accuracy across internal warehouses, manufacturing sites, contract manufacturers, third-party logistics providers, and other partner locations. This role owns recurring inventory reporting, identifies discrepancies and trends, supports cycle count execution, and partners cross-functionally to close the physical-to-system lag, prevent recurring variances, and reduce inventory loss, write-offs, and operational risk .
The ideal candidate has experience in a complex, fast-paced manufacturing, logistics, or supply chain environment and understands how physical inventory movement, system transactions, and financial controls must stay aligned. This person must be highly analytical, detail-oriented, self-directed, and able to collaborate effectively with partner teams, resolve conflicts professionally, and drive outcomes without direct authority.
Key Responsibilities
Create, maintain, and improve recurring inventory reports, dashboards, and scorecards that measure inventory accuracy, cycle count completion, variance trends, exception aging, transaction timing, inventory movement posting discipline, and location-level discrepancies.
Analyze inventory data across multiple sites and partner nodes to identify physical-to-system mismatches, root causes, recurring process gaps, and areas of financial or operational exposure.
Support cycle count planning and execution, including count schedules, count readiness, discrepancy tracking, recount coordination, variance validation, and closure reporting.
Monitor cycle count adherence by site and inventory category, ensuring high-priority materials are counted on the required cadence and variances are investigated, documented, and closed timely.
Partner with Inventory, Logistics, Warehouse, Manufacturing, Finance, Supply Chain, Contract Manufacturers, and 3PL teams to investigate discrepancies and drive corrective actions to completion.
Collaborate closely and effectively with internal and external partner teams, using clear communication, professional judgment, and structured follow-up to resolve issues, align priorities, and address conflicts in a respectful and productive manner.
Monitor high-value and high-risk inventory, including A/B class items, serialized material, RMA inventory, MRB, scrap, consigned inventory, in-transit material, and partner-held stock.
Reconcile inventory balances between ERP, WMS, partner reports, physical counts, transfer records, receiving records, and shipment evidence.
Track open exceptions such as aged transfer orders, pending receipts, unresolved count variances, unposted movements, duplicate receipts, inventory holds, RMA activity, scrap, unbuild activity, and aging inventory requiring disposition.
Develop actionable reporting that helps leadership prioritize risk, improve controls, reduce manual reconciliation, and make informed operational decisions.
Build reporting that separates operational accuracy from financial exposure, allowing leadership to see unit, location, transaction, and aging risks without displaying confidential inventory value.
Support inventory control best practices, including ABC categorization, risk-based count prioritization, location-level accuracy reporting, reason-code discipline, transaction cutoffs, blind counts, segregation of duties, audit-ready evidence retention, and clear exception ownership.
Assist with month-end, quarter-end, and year-end inventory readiness by identifying open issues, reporting financial exposure, and ensuring timely follow-up on required actions.
Maintain audit-ready documentation for custody, receipts, counts, adjustments, approvals, root-cause decisions, and corrective actions to support operational controls and compliance readiness.
Identify, create, govern, and iterate inventory control processes as business needs, site requirements, reporting maturity, and operational complexity evolve in a fast and quickly changing environment.
Required Qualifications
3+ years of experience in inventory analysis, inventory control, manufacturing operations, logistics, supply chain operations, warehouse operations, or a related field.
Strong understanding of inventory practices, including cycle counting, variance analysis, inventory adjustments, inventory reconciliation, receiving, transfers, scrap, MRB, RMA, and physical inventory controls.
Experience working in a complex, fast-paced environment with multiple sites, warehouses, contract manufacturers, 3PLs, or external partners.
Advanced Excel or spreadsheet skills, including lookups, pivot tables, formulas, data comparisons, exception reporting, and large-data-set analysis.
Experience with ERP, WMS, or inventory reporting systems; NetSuite experience is preferred.
Ability to translate data into practical business insights, corrective actions, and clear recommendations for operational leaders.
Strong attention to detail, follow-through, ownership, and ability to manage multiple priorities with limited supervision.
Effective written and verbal communication skills, with the ability to influence cross-functional teams and drive outcomes without direct authority.
Basic understanding of supply chain practices, including purchasing, receiving, manufacturing flow, inventory movement, logistics, and partner inventory management.
KEY PERFORMANCE INDICATORS
Cycle Count Completion
Target: 99%+ completion on time, by site, category, and count schedule.
Inventory Record Accuracy
Target: 99%+ accuracy, measured by unit, location, item-level variance, transaction integrity, and count-to-system alignment.
High-Value Inventory Coverage
Target: 100% of high-priority, high-risk, or A/B inventory counted on the required cadence, without disclosing confidential inventory values.
Adjustment and Write-Off Reduction
Target: Minimize inventory loss, write-offs, avoidable adjustments, and recurring variance exposure.
Exception Aging
Target: Reduce aged transfer orders, pending receipts, unresolved variances, inventory holds, reconciliation defects, and open exception queues.
Transaction Timeliness
Target: Support same-day or 24-hour posting discipline for physical inventory movements, where applicable.
Root-Cause Closure
Target: Ensure material variances include a documented root cause, owner, corrective action, and closure date.
Reporting Quality
Target: Deliver accurate, timely, and actionable reports that clearly identify risk, trends, owners, next steps, and escalation paths while protecting confidential inventory valuation data.
Best-Practice Expectations
Use ABC classification and risk-based prioritization to focus controls on the inventory that carries the highest financial, operational, or customer-impact risk.
Separate financial accuracy from operational accuracy by reporting both value variance and physical/location variance.
Maintain clear ownership for every exception, including due dates, root cause, corrective action, and escalation path.
Use standardized reason codes and supporting evidence for adjustments, scrap, write-offs, inventory holds, and other inventory-impacting transactions.
Promote clean transaction timing by aligning physical movement, ERP/WMS updates, and supporting documentation.
Support audit readiness through complete count records, approval evidence, reconciliation support, and clear documentation of variance decisions.
Collaborate with internal and external partners to improve reporting cadence, reduce manual work, and create repeatable inventory control processes.
Work through ambiguity and competing priorities with partner teams by clarifying ownership, escalating risks appropriately, and maintaining professional, solutions-oriented communication.
Key Competencies
Data-driven problem solving
Inventory accuracy and control mindset
Strong ownership and follow-through
Ability to self-direct in ambiguous environments
Cross-functional collaboration and influence without authority
Manufacturing logistics and supply chain awareness
Attention to detail and reporting discipline
Sense of urgency and ability to operate in a fast-paced environment
Professional conflict resolution and partner-team alignment
Ability to build, govern, and continuously improve processes in a rapidly changing environment
This job description is not intended to be an exhaustive list of responsibilities. The Inventory Analyst is expected to proactively identify gaps, create scalable processes, govern execution standards, and continuously improve reporting and control practices as business needs evolve.
The base salary range for this position is $150,000 to $220,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nPosition Summary\n\nThe Inventory Analyst is responsible for using data, reporting, and operational analysis to improve inventory accuracy across internal warehouses, manufacturing sites, contract manufacturers, third-party logistics providers, and other partner locations. This role owns recurring inventory reporting, identifies discrepancies and trends, supports cycle count execution, and partners cross-functionally to close the physical-to-system lag, prevent recurring variances, and reduce inventory loss, write-offs, and operational risk .\n\nThe ideal candidate has experience in a complex, fast-paced manufacturing, logistics, or supply chain environment and understands how physical inventory movement, system transactions, and financial controls must stay aligned. This person must be highly analytical, detail-oriented, self-directed, and able to collaborate effectively with partner teams, resolve conflicts professionally, and drive outcomes without direct authority.\n\nKey Responsibilities\n\n - Create, maintain, and improve recurring inventory reports, dashboards, and scorecards that measure inventory accuracy, cycle count completion, variance trends, exception aging, transaction timing, inventory movement posting discipline, and location-level discrepancies.\n\n - Analyze inventory data across multiple sites and partner nodes to identify physical-to-system mismatches, root causes, recurring process gaps, and areas of financial or operational exposure.\n\n - Support cycle count planning and execution, including count schedules, count readiness, discrepancy tracking, recount coordination, variance validation, and closure reporting.\n\n - Monitor cycle count adherence by site and inventory category, ensuring high-priority materials are counted on the required cadence and variances are investigated, documented, and closed timely.\n\n - Partner with Inventory, Logistics, Warehouse, Manufacturing, Finance, Supply Chain, Contract Manufacturers, and 3PL teams to investigate discrepancies and drive corrective actions to completion.\n\n - Collaborate closely and effectively with internal and external partner teams, using clear communication, professional judgment, and structured follow-up to resolve issues, align priorities, and address conflicts in a respectful and productive manner.\n\n - Monitor high-value and high-risk inventory, including A/B class items, serialized material, RMA inventory, MRB, scrap, consigned inventory, in-transit material, and partner-held stock.\n\n - Reconcile inventory balances between ERP, WMS, partner reports, physical counts, transfer records, receiving records, and shipment evidence.\n\n - Track open exceptions such as aged transfer orders, pending receipts, unresolved count variances, unposted movements, duplicate receipts, inventory holds, RMA activity, scrap, unbuild activity, and aging inventory requiring disposition.\n\n - Develop actionable reporting that helps leadership prioritize risk, improve controls, reduce manual reconciliation, and make informed operational decisions.\n\n - Build reporting that separates operational accuracy from financial exposure, allowing leadership to see unit, location, transaction, and aging risks without displaying confidential inventory value.\n\n - Support inventory control best practices, including ABC categorization, risk-based count prioritization, location-level accuracy reporting, reason-code discipline, transaction cutoffs, blind counts, segregation of duties, audit-ready evidence retention, and clear exception ownership.\n\n - Assist with month-end, quarter-end, and year-end inventory readiness by identifying open issues, reporting financial exposure, and ensuring timely follow-up on required actions.\n\n - Maintain audit-ready documentation for custody, receipts, counts, adjustments, approvals, root-cause decisions, and corrective actions to support operational controls and compliance readiness.\n\n - Identify, create, govern, and iterate inventory control processes as business needs, site requirements, reporting maturity, and operational complexity evolve in a fast and quickly changing environment.\n\nRequired Qualifications\n\n - 3+ years of experience in inventory analysis, inventory control, manufacturing operations, logistics, supply chain operations, warehouse operations, or a related field.\n\n - Strong understanding of inventory practices, including cycle counting, variance analysis, inventory adjustments, inventory reconciliation, receiving, transfers, scrap, MRB, RMA, and physical inventory controls.\n\n - Experience working in a complex, fast-paced environment with multiple sites, warehouses, contract manufacturers, 3PLs, or external partners.\n\n - Advanced Excel or spreadsheet skills, including lookups, pivot tables, formulas, data comparisons, exception reporting, and large-data-set analysis.\n\n - Experience with ERP, WMS, or inventory reporting systems; NetSuite experience is preferred.\n\n - Ability to translate data into practical business insights, corrective actions, and clear recommendations for operational leaders.\n\n - Strong attention to detail, follow-through, ownership, and ability to manage multiple priorities with limited supervision.\n\n - Effective written and verbal communication skills, with the ability to influence cross-functional teams and drive outcomes without direct authority.\n\n - Basic understanding of supply chain practices, including purchasing, receiving, manufacturing flow, inventory movement, logistics, and partner inventory management.\n\nKEY PERFORMANCE INDICATORS\n\n 1. Cycle Count Completion\n Target: 99%+ completion on time, by site, category, and count schedule.\n\n 2. Inventory Record Accuracy\n Target: 99%+ accuracy, measured by unit, location, item-level variance, transaction integrity, and count-to-system alignment.\n\n 3. High-Value Inventory Coverage\n Target: 100% of high-priority, high-risk, or A/B inventory counted on the required cadence, without disclosing confidential inventory values.\n\n 4. Adjustment and Write-Off Reduction\n Target: Minimize inventory loss, write-offs, avoidable adjustments, and recurring variance exposure.\n\n 5. Exception Aging\n Target: Reduce aged transfer orders, pending receipts, unresolved variances, inventory holds, reconciliation defects, and open exception queues.\n\n 6. Transaction Timeliness\n Target: Support same-day or 24-hour posting discipline for physical inventory movements, where applicable.\n\n 7. Root-Cause Closure\n Target: Ensure material variances include a documented root cause, owner, corrective action, and closure date.\n\n 8. Reporting Quality\n Target: Deliver accurate, timely, and actionable reports that clearly identify risk, trends, owners, next steps, and escalation paths while protecting confidential inventory valuation data.\n\nBest-Practice Expectations\n\n - Use ABC classification and risk-based prioritization to focus controls on the inventory that carries the highest financial, operational, or customer-impact risk.\n\n - Separate financial accuracy from operational accuracy by reporting both value variance and physical/location variance.\n\n - Maintain clear ownership for every exception, including due dates, root cause, corrective action, and escalation path.\n\n - Use standardized reason codes and supporting evidence for adjustments, scrap, write-offs, inventory holds, and other inventory-impacting transactions.\n\n - Promote clean transaction timing by aligning physical movement, ERP/WMS updates, and supporting documentation.\n\n - Support audit readiness through complete count records, approval evidence, reconciliation support, and clear documentation of variance decisions.\n\n - Collaborate with internal and external partners to improve reporting cadence, reduce manual work, and create repeatable inventory control processes.\n\nWork through ambiguity and competing priorities with partner teams by clarifying ownership, escalating risks appropriately, and maintaining professional, solutions-oriented communication.\n\nKey Competencies\n\n - Data-driven problem solving\n\n - Inventory accuracy and control mindset\n\n - Strong ownership and follow-through\n\n - Ability to self-direct in ambiguous environments\n\n - Cross-functional collaboration and influence without authority\n\n - Manufacturing logistics and supply chain awareness\n\n - Attention to detail and reporting discipline\n\n - Sense of urgency and ability to operate in a fast-paced environment\n\n - Professional conflict resolution and partner-team alignment\n\n - Ability to build, govern, and continuously improve processes in a rapidly changing environment\n\nThis job description is not intended to be an exhaustive list of responsibilities. The Inventory Analyst is expected to proactively identify gaps, create scalable processes, govern execution standards, and continuously improve reporting and control practices as business needs evolve.\n\n \n\nThe base salary range for this position is $150,000 to $220,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"522004b6-8ac2-445c-969f-d33035fef794","title":"Accounting Manager","department":"Corporate","team":"Finance","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2026-08-19T18:34:17.135+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressRegion":"California ","addressCountry":"United States","addressLocality":"Sunnyvale "}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/522004b6-8ac2-445c-969f-d33035fef794","applyUrl":"https://jobs.ashbyhq.com/cerebras/522004b6-8ac2-445c-969f-d33035fef794/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About the Role
We are seeking a detail-oriented and experienced Accounting Manager to join our corporate accounting team. This role is responsible for managing and maintaining general ledger accounting operations, ensuring accurate and timely financial reporting in compliance with U.S. GAAP.
Manage the monthly, quarterly, and annual financial statement close processes globally in accordance with US GAAP, including preparation and review of journal entries, account reconciliations, and variance analysis for cash, prepaids, accruals, inter-company, OPEX and various other accounts.
Develop and implement the accounting strategy and framework for new international entities upon business growth.
Enhance and standardize accounting policies, procedures and reporting processes across our global operations.
Manage relationships with external accounting service providers and other internal stakeholders to support the accounting operations of international entities.
Support the external reporting function by providing account reconciliation and analysis reports for statements of cash flow and financial statement footnotes and disclosures preparation.
Support quarterly, annual and interim external audits including preparation of audit schedules and responding to auditor requests
Support Assistant Controller and Senior Accounting Manager for the day-to-day financial activities (including chart of accounts maintenance, foreign subsidiaries, and intercompany accounting) for accuracy while ensuring compliance with US GAAP, local statutory accounting requirements and internal policies
Maintain effective internal controls over general ledger accounting records including account reconciliations and journal entries
Support state sales and use taxes filing quarterly; semi-annually; or annually for CA and other states by providing sales and purchase transactions to Avalara (online sales and use taxes filing tool)
Collaborate with other departments to ensure that accounting information is accurate and timely
Implement best practices and ensure compliance with US GAAP, and policies and procedures
Ad hoc projects as needed
Bachelor’s degree in accounting, Finance, or related field (required)
CPA certification (preferred)
5+ years of progressive accounting experience, including 2+ years in a public company with consolidation and multi-entity reporting environment is preferred
Ability to solve problems and work with large volumes of data
Must have an understanding of internal controls and auditing processes
Proficiency in ERP systems skills (i.e. NetSuite)
Advanced Microsoft Excel skills; ability to work with large data sets and pivot tables
Strong communication and collaboration skills to work cross-functionally
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout the Role \n\nWe are seeking a detail-oriented and experienced Accounting Manager to join our corporate accounting team. This role is responsible for managing and maintaining general ledger accounting operations, ensuring accurate and timely financial reporting in compliance with U.S. GAAP.\n\n\nRESPONSIBILITIES\n\n - Manage the monthly, quarterly, and annual financial statement close processes globally in accordance with US GAAP, including preparation and review of journal entries, account reconciliations, and variance analysis for cash, prepaids, accruals, inter-company, OPEX and various other accounts.\n\n - Develop and implement the accounting strategy and framework for new international entities upon business growth.\n\n - Enhance and standardize accounting policies, procedures and reporting processes across our global operations.\n\n - Manage relationships with external accounting service providers and other internal stakeholders to support the accounting operations of international entities.\n\n - Support the external reporting function by providing account reconciliation and analysis reports for statements of cash flow and financial statement footnotes and disclosures preparation.\n\n - Support quarterly, annual and interim external audits including preparation of audit schedules and responding to auditor requests\n\n - Support Assistant Controller and Senior Accounting Manager for the day-to-day financial activities (including chart of accounts maintenance, foreign subsidiaries, and intercompany accounting) for accuracy while ensuring compliance with US GAAP, local statutory accounting requirements and internal policies\n\n - Maintain effective internal controls over general ledger accounting records including account reconciliations and journal entries\n\n - Support state sales and use taxes filing quarterly; semi-annually; or annually for CA and other states by providing sales and purchase transactions to Avalara (online sales and use taxes filing tool)\n\n - Collaborate with other departments to ensure that accounting information is accurate and timely\n\n - Implement best practices and ensure compliance with US GAAP, and policies and procedures\n\n - Ad hoc projects as needed\n\n\nSKILLS & QUALIFICATIONS\n\n - Bachelor’s degree in accounting, Finance, or related field (required)\n\n - CPA certification (preferred)\n\n - 5+ years of progressive accounting experience, including 2+ years in a public company with consolidation and multi-entity reporting environment is preferred\n\n - Ability to solve problems and work with large volumes of data\n\n - Must have an understanding of internal controls and auditing processes\n\n - Proficiency in ERP systems skills (i.e. NetSuite)\n\n - Advanced Microsoft Excel skills; ability to work with large data sets and pivot tables\n\n - Strong communication and collaboration skills to work cross-functionally\n\n\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"b1026ed1-1134-48cc-a8ad-780241ca7651","title":"Data Center Provisioning Engineer ","department":"Datacenters","team":"Datacenters","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[{"location":"Norway","address":{"postalAddress":{"addressRegion":"Norway ","addressCountry":"Norway"}}},{"location":"Toronto, CAN","address":{"postalAddress":{"addressRegion":"Ontario ","addressCountry":"Canada","addressLocality":"Toronto "}}},{"location":"Finland","address":{"postalAddress":{"addressRegion":"Finland","addressCountry":"Finland"}}}],"publishedAt":"2026-08-18T16:16:25.911+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressRegion":"California ","addressCountry":"United States","addressLocality":"Sunnyvale "}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/b1026ed1-1134-48cc-a8ad-780241ca7651","applyUrl":"https://jobs.ashbyhq.com/cerebras/b1026ed1-1134-48cc-a8ad-780241ca7651/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
The Data Center Provisioning Engineer will be responsible for provisioning, commissioning, and validating network infrastructure, servers, and related systems across large-scale data center deployments. This role works closely with engineering teams, data center technicians, vendors, and operations teams to bring new sites and infrastructure online quickly and reliably. The ideal candidate combines strong networking and systems expertise with automation, troubleshooting, and a focus on building repeatable processes that scale across multiple parallel deployments.
Provision and configure network devices, firewalls, and servers in data centers by following documented processes and using purpose-built provisioning frameworks and automation tools.
Troubleshoot and resolve server, network, configuration, automation, and connectivity issues encountered during infrastructure provisioning and service bring-up.
Collaborate with engineering teams, data center technicians, cabling vendors, and rack integrators to coordinate infrastructure deployment and ensure timely site readiness.
Support network, power, and mechanical commissioning, including testing and validation of network connectivity, device configurations, server readiness, and infrastructure dependencies.
Develop and continuously improve provisioning processes, tooling, and automation to enable reliable, repeatable, and scalable deployment across multiple sites in parallel.
Perform post-deployment validation and support integration with monitoring, alerting, and operational tooling to ensure infrastructure meets production-readiness requirements.
Coordinate the successful handoff of deployed infrastructure to Operations & Maintenance (O&M) teams - Cluster Operations, Network Operations, Site Operations.
Document deployment procedures, troubleshooting findings, lessons learned, and process improvements to increase deployment efficiency and reliability.
Bachelor's degree in Electrical Engineering, Computer Science, Computer Engineering, or a related technical field.
At least 5 years of relevant experience in network device and server provisioning, data center infrastructure, Site Reliability Engineering (SRE), or a related field.
Strong hands-on experience with server and network device provisioning and troubleshooting, including diagnosing issues across compute, networking, operating systems, configuration, and automation layers.
Proficiency in Python and shell scripting, with experience using automation to streamline infrastructure deployment.
Hands-on experience with at least one major cloud platform—AWS, GCP, or Azure—and with Kubernetes, including deployment, scaling, troubleshooting, and cluster management.
Experience with Infrastructure as Code (IaC) and configuration management technologies, particularly Terraform and Ansible.
Strong knowledge of fundamentals and technologies, including PXE, DNS, DHCP, TCP/IP, load balancing, VPCs, firewalls, VLANs, LACP, BGP, and OSPF.
Experience upgrading server firmware, switch software OS, and PDU firmware
Strong problem-solving, communication, collaboration, and documentation skills, with the ability to work effectively across engineering, operations, field, and vendor teams in fast-paced data center deployment environments.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n\n\n\nROLE\n\n\nThe Data Center Provisioning Engineer will be responsible for provisioning, commissioning, and validating network infrastructure, servers, and related systems across large-scale data center deployments. This role works closely with engineering teams, data center technicians, vendors, and operations teams to bring new sites and infrastructure online quickly and reliably. The ideal candidate combines strong networking and systems expertise with automation, troubleshooting, and a focus on building repeatable processes that scale across multiple parallel deployments.\n\n\n\nRESPONSIBILITIES\n\n - Provision and configure network devices, firewalls, and servers in data centers by following documented processes and using purpose-built provisioning frameworks and automation tools.\n\n - Troubleshoot and resolve server, network, configuration, automation, and connectivity issues encountered during infrastructure provisioning and service bring-up.\n\n - Collaborate with engineering teams, data center technicians, cabling vendors, and rack integrators to coordinate infrastructure deployment and ensure timely site readiness.\n\n - Support network, power, and mechanical commissioning, including testing and validation of network connectivity, device configurations, server readiness, and infrastructure dependencies.\n\n - Develop and continuously improve provisioning processes, tooling, and automation to enable reliable, repeatable, and scalable deployment across multiple sites in parallel.\n\n - Perform post-deployment validation and support integration with monitoring, alerting, and operational tooling to ensure infrastructure meets production-readiness requirements.\n\n - Coordinate the successful handoff of deployed infrastructure to Operations & Maintenance (O&M) teams - Cluster Operations, Network Operations, Site Operations.\n\n - Document deployment procedures, troubleshooting findings, lessons learned, and process improvements to increase deployment efficiency and reliability.\n\n \n\n\nREQUIREMENTS:\n\n - Bachelor's degree in Electrical Engineering, Computer Science, Computer Engineering, or a related technical field.\n\n - At least 5 years of relevant experience in network device and server provisioning, data center infrastructure, Site Reliability Engineering (SRE), or a related field.\n\n - Strong hands-on experience with server and network device provisioning and troubleshooting, including diagnosing issues across compute, networking, operating systems, configuration, and automation layers.\n\n - Proficiency in Python and shell scripting, with experience using automation to streamline infrastructure deployment.\n\n - Hands-on experience with at least one major cloud platform—AWS, GCP, or Azure—and with Kubernetes, including deployment, scaling, troubleshooting, and cluster management.\n\n - Experience with Infrastructure as Code (IaC) and configuration management technologies, particularly Terraform and Ansible.\n\n - Strong knowledge of fundamentals and technologies, including PXE, DNS, DHCP, TCP/IP, load balancing, VPCs, firewalls, VLANs, LACP, BGP, and OSPF.\n\n - Experience upgrading server firmware, switch software OS, and PDU firmware\n\n - Strong problem-solving, communication, collaboration, and documentation skills, with the ability to work effectively across engineering, operations, field, and vendor teams in fast-paced data center deployment environments.\n \n \n\n\nLOCATION: NORWAY | FINLAND | TORONTO | SUNNYVALE\n\n\n\n \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"453a7940-ba08-4656-b9a7-eb3d3fd28db2","title":"Head of SOX Internal Audit ","department":"Corporate","team":"Finance","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[{"location":"Remote (US)","address":{"postalAddress":{"addressCountry":"United States"}}}],"publishedAt":"2026-08-19T15:20:17.959+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressRegion":"California ","addressCountry":"United States","addressLocality":"Sunnyvale "}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/453a7940-ba08-4656-b9a7-eb3d3fd28db2","applyUrl":"https://jobs.ashbyhq.com/cerebras/453a7940-ba08-4656-b9a7-eb3d3fd28db2/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
The Head of SOX & Internal Audit will establish and lead the Company's SOX compliance program and eventually progress towards establishing the Internal Audit function. This individual will serve as a trusted advisor to executive leadership and the Audit Committee, providing independent assurance regarding the effectiveness of governance, risk management, internal controls, financial reporting processes, cybersecurity controls, and operational risk management.
The successful candidate will build a scalable, risk-based Internal Audit program aligned with Institute of Internal Auditors (IIA) standards and will oversee SOX Section 404 compliance, internal control testing, deficiency remediation, and enterprise risk assessments. The role requires strong leadership, technical expertise, and the ability to partner effectively across Finance, IT, Legal, Operations, Engineering, Security, and executive management. This role aligns with Cerebras' roadmap to create clear separation between Controllership and Independent Testing and to support ongoing compliance as a public company.
Key Responsibilities
SOX & Internal Audit Program Leadership
Own the design, implementation, and ongoing operation of the SOX compliance program.
Lead annual SOX risk assessments, scoping, materiality considerations, and control rationalization efforts.
Oversee documentation and maintenance of narratives, flowcharts, risk-control matrices (RCMs), and process inventories.
Direct walkthroughs, control testing, deficiency evaluation, remediation validation, and management reporting.
Coordinate with Finance, IT, Legal, Security, Engineering, and business process owners to maintain effective internal controls over financial reporting (ICFR).
Monitor remediation efforts and ensure timely resolution of control deficiencies.
Drive continuous improvement through automation, control optimization, and reduction of manual testing.
Support management's SOX Sections 302 and 404 certification processes.
Establish and lead the Internal Audit function, charter, methodology, policies, and annual audit planning process.
Develop and execute a risk-based audit plan covering financial, operational, technology, cybersecurity, compliance, and strategic risks.
Present audit plans, audit results, risk assessments, and emerging risks to executive leadership and the Audit Committee.
Governance, Risk, and Compliance
Assist leadership in strengthening enterprise risk management and governance processes.
Evaluate entity-level controls and the overall control environment.
Support fraud risk assessments and development of monitoring programs.
Assess risks associated with rapidly scaling AI infrastructure, data centers, supply chain operations, manufacturing, inventory management, cybersecurity, export controls, and global operations.
Review regulatory compliance programs and provide independent assurance over key compliance obligations.
Partner with Legal and Compliance functions regarding investigations, whistleblower matters, and governance initiatives.
External Auditor & Audit Committee Engagement
Serve as principal liaison with external auditors on internal control, SOX, and audit matters.
Facilitate reliance strategies and coordination activities between Internal Audit and external auditors where appropriate.
Prepare Audit Committee materials and provide executive-level reporting on risks, audit findings, and remediation activities.
Support Board governance initiatives and audit committee oversight responsibilities.
Organizational Development
Build a high-performing Internal Audit organization capable of supporting a public-company environment.
Develop talent, audit methodologies, and technology-enabled audit capabilities.
Champion a culture of accountability, ethical conduct, control awareness, and continuous improvement.
Internal Audit Leadership
Ensure the Internal Audit function operates in accordance with IIA Global Internal Audit Standards.
Develop internal audit methodologies, quality assurance processes, and reporting frameworks.
Build and manage an Internal Audit team, including co-sourced providers and external consultants as needed.
Identify emerging risks and recommend practical, business-focused mitigation strategies.
Qualifications
Bachelor's degree in Accounting, Finance, Information Systems, or related field.
10+ years of progressive experience in Internal Audit, SOX compliance, Risk Advisory, or public accounting.
5+ years in leadership roles managing audit teams and enterprise-wide audit programs.
Deep knowledge of:
Sarbanes-Oxley Act (SOX)
COSO Framework
SEC reporting requirements
Internal Controls over Financial Reporting (ICFR)
Enterprise Risk Management
IIA Standards
Experience building or transforming Internal Audit and SOX programs at public companies or IPO-stage organizations.
Strong understanding of IT general controls (ITGCs), cybersecurity risks, and technology-enabled business processes.
Experience presenting to Audit Committees, CFOs, CAOs, and Boards of Directors.
Preferred
CPA, CIA, CISA, or equivalent professional certification.
Big Four or national public accounting firm experience.
Semiconductor, hardware, manufacturing, cloud infrastructure, AI, or technology industry experience.
Proven ability to design, implement, and mature SOX and Internal Audit programs from inception through steady-state operation.
Experience with ERP environments such as NetSuite, Oracle, SAP, or equivalent.
Experience implementing data analytics and audit automation tools.
Success Metrics (First 12–18 Months)
Implement sustainable SOX governance structure and testing methodology.
Improve control maturity and remediation management across key business processes.
Achieve external auditor reliance on management testing where appropriate.
Deliver meaningful audit insights to leadership and the Audit Committee.
Establish Internal Audit function, charter, policies, and reporting structure.
Complete enterprise risk assessment and risk-based audit plan.
Leadership Competencies
Executive presence and board-level communication skills.
Independent judgment and professional skepticism.
Strategic thinker with strong business acumen.
Ability to influence across highly technical and cross-functional organizations.
Exceptional project management and organizational skills.
Strong commitment to integrity, objectivity, and continuous improvement.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n\nABOUT THE ROLE\n\nThe Head of SOX & Internal Audit will establish and lead the Company's SOX compliance program and eventually progress towards establishing the Internal Audit function. This individual will serve as a trusted advisor to executive leadership and the Audit Committee, providing independent assurance regarding the effectiveness of governance, risk management, internal controls, financial reporting processes, cybersecurity controls, and operational risk management.\n\nThe successful candidate will build a scalable, risk-based Internal Audit program aligned with Institute of Internal Auditors (IIA) standards and will oversee SOX Section 404 compliance, internal control testing, deficiency remediation, and enterprise risk assessments. The role requires strong leadership, technical expertise, and the ability to partner effectively across Finance, IT, Legal, Operations, Engineering, Security, and executive management. This role aligns with Cerebras' roadmap to create clear separation between Controllership and Independent Testing and to support ongoing compliance as a public company.\n\nKey Responsibilities\n\nSOX & Internal Audit Program Leadership\n\n - Own the design, implementation, and ongoing operation of the SOX compliance program.\n\n - Lead annual SOX risk assessments, scoping, materiality considerations, and control rationalization efforts.\n\n - Oversee documentation and maintenance of narratives, flowcharts, risk-control matrices (RCMs), and process inventories.\n\n - Direct walkthroughs, control testing, deficiency evaluation, remediation validation, and management reporting.\n\n - Coordinate with Finance, IT, Legal, Security, Engineering, and business process owners to maintain effective internal controls over financial reporting (ICFR).\n\n - Monitor remediation efforts and ensure timely resolution of control deficiencies.\n\n - Drive continuous improvement through automation, control optimization, and reduction of manual testing.\n\n - Support management's SOX Sections 302 and 404 certification processes.\n\n - Establish and lead the Internal Audit function, charter, methodology, policies, and annual audit planning process.\n\n - Develop and execute a risk-based audit plan covering financial, operational, technology, cybersecurity, compliance, and strategic risks.\n\n - Present audit plans, audit results, risk assessments, and emerging risks to executive leadership and the Audit Committee.\n\nGovernance, Risk, and Compliance\n\n - Assist leadership in strengthening enterprise risk management and governance processes.\n\n - Evaluate entity-level controls and the overall control environment.\n\n - Support fraud risk assessments and development of monitoring programs.\n\n - Assess risks associated with rapidly scaling AI infrastructure, data centers, supply chain operations, manufacturing, inventory management, cybersecurity, export controls, and global operations.\n\n - Review regulatory compliance programs and provide independent assurance over key compliance obligations.\n\n - Partner with Legal and Compliance functions regarding investigations, whistleblower matters, and governance initiatives.\n\nExternal Auditor & Audit Committee Engagement\n\n - Serve as principal liaison with external auditors on internal control, SOX, and audit matters.\n\n - Facilitate reliance strategies and coordination activities between Internal Audit and external auditors where appropriate.\n\n - Prepare Audit Committee materials and provide executive-level reporting on risks, audit findings, and remediation activities.\n\n - Support Board governance initiatives and audit committee oversight responsibilities.\n\nOrganizational Development\n\n - Build a high-performing Internal Audit organization capable of supporting a public-company environment.\n\n - Develop talent, audit methodologies, and technology-enabled audit capabilities.\n\n - Champion a culture of accountability, ethical conduct, control awareness, and continuous improvement.\n\nInternal Audit Leadership\n\n - Ensure the Internal Audit function operates in accordance with IIA Global Internal Audit Standards.\n\n - Develop internal audit methodologies, quality assurance processes, and reporting frameworks.\n\n - Build and manage an Internal Audit team, including co-sourced providers and external consultants as needed.\n\n - Identify emerging risks and recommend practical, business-focused mitigation strategies. \n\nQualifications\n\n - Bachelor's degree in Accounting, Finance, Information Systems, or related field.\n\n - 10+ years of progressive experience in Internal Audit, SOX compliance, Risk Advisory, or public accounting.\n\n - 5+ years in leadership roles managing audit teams and enterprise-wide audit programs.\n\n - Deep knowledge of:\n\n - Sarbanes-Oxley Act (SOX)\n\n - COSO Framework\n\n - SEC reporting requirements\n\n - Internal Controls over Financial Reporting (ICFR)\n\n - Enterprise Risk Management\n\n - IIA Standards\n\n - Experience building or transforming Internal Audit and SOX programs at public companies or IPO-stage organizations.\n\n - Strong understanding of IT general controls (ITGCs), cybersecurity risks, and technology-enabled business processes.\n\n - Experience presenting to Audit Committees, CFOs, CAOs, and Boards of Directors.\n\nPreferred\n\n - CPA, CIA, CISA, or equivalent professional certification.\n\n - Big Four or national public accounting firm experience.\n\n - Semiconductor, hardware, manufacturing, cloud infrastructure, AI, or technology industry experience.\n\n - Proven ability to design, implement, and mature SOX and Internal Audit programs from inception through steady-state operation.\n\n - Experience with ERP environments such as NetSuite, Oracle, SAP, or equivalent.\n\n - Experience implementing data analytics and audit automation tools.\n\nSuccess Metrics (First 12–18 Months)\n\n - Implement sustainable SOX governance structure and testing methodology.\n\n - Improve control maturity and remediation management across key business processes.\n\n - Achieve external auditor reliance on management testing where appropriate.\n\n - Deliver meaningful audit insights to leadership and the Audit Committee.\n\n - Establish Internal Audit function, charter, policies, and reporting structure.\n\n - Complete enterprise risk assessment and risk-based audit plan.\n\nLeadership Competencies\n\n - Executive presence and board-level communication skills.\n\n - Independent judgment and professional skepticism.\n\n - Strategic thinker with strong business acumen.\n\n - Ability to influence across highly technical and cross-functional organizations.\n\n - Exceptional project management and organizational skills.\n\n - Strong commitment to integrity, objectivity, and continuous improvement.\n\n\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"d4eed58d-bd1c-496e-a3b3-d0e34e65af83","title":"Staff Business Systems Analyst","department":"IT & Security","team":"IT","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2026-08-20T01:29:19.879+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressRegion":"California ","addressCountry":"United States","addressLocality":"Sunnyvale "}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/d4eed58d-bd1c-496e-a3b3-d0e34e65af83","applyUrl":"https://jobs.ashbyhq.com/cerebras/d4eed58d-bd1c-496e-a3b3-d0e34e65af83/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Scope: Enterprise business processes and systems across BIS-supported functions
Role Overview
We are looking for a Staff Business Systems Analyst who can connect business strategy, process design, enterprise systems, and technology delivery across the functions supported by Business Intelligence & Systems (BIS). This role serves as a senior functional partner to business teams and translates complex needs into clear business cases, process designs, functional specifications, and sprint-ready work. The role partners closely with functional leaders, BIS Architecture, Engineering, Data, Production Support, and external vendors to deliver scalable, well-controlled, and supportable business capabilities.
Key Responsibilities
• Partner with the functional leaders to shape executive roadmaps, business cases, intake, prioritization, and measurable business outcomes.
• Lead discovery, current-state and future-state process mapping, root-cause analysis, and gap assessment across Finance, Supply Chain and Distribution Center Operations, People and Legal, and emerging business areas as needed.
• Translate business needs into functional requirements, process and data flows, user stories, acceptance criteria, product specifications, and sprint-ready backlog items.
• Develop functional depth in the applications and processes within assigned domains, including ERP and other enterprise platforms, integrations, reporting, controls, and downstream data dependencies.
• Facilitate cross-functional design sessions with Technical Architecture and Engineering, evaluate solution tradeoffs, drive decisions, and ensure designs align with enterprise standards, integration strategy, and long-term scalability.
• Maintain requirements traceability and lead functional validation, user acceptance testing, defect triage, release readiness, training, and adoption activities.
• Embed compliance, segregation-of-duties, auditability, security, data quality, and operational controls into process and system designs, particularly in a public-company environment.
• Analyze production issues as needed and business-process KPIs, define durable improvements, and coordinate clear handoffs to Engineering and Production Support.
• Lead or support vendor evaluations and contribute functional leadership throughout solution selection, implementation, and post-launch stabilization.
• Identify practical opportunities for workflow automation and AI-enabled capabilities while maintaining appropriate controls, transparency, and business ownership.
• Raise the quality of business analysis across BIS by establishing reusable standards, coaching peers, and modeling structured, outcome-oriented problem solving across multiple domains.
Background We're Looking For
• Proven experience in a senior Business Systems Analyst, Business Process, Product, Program, or comparable enterprise-systems role.
• Demonstrated success leading end-to-end business transformations across process, technology, data, controls, and change adoption.
• Strong functional depth in one or more enterprise domains such as Finance, Supply Chain and Distribution Center Operations, People, Legal, or other corporate functions, with the ability to learn additional domains quickly.
• Strong hands-on experience with enterprise applications such as ERP and adjacent business platforms; experience with integrations, analytics, reporting, and workflow automation is highly valued.
• Strong command of business-analysis practices, including process modeling, requirements elicitation, functional specifications, user stories, acceptance criteria, UAT, and release readiness.
• Technical fluency sufficient to work effectively with architects, engineers, integration teams, data teams, and vendors; an engineering or technical background is a plus.
• Experience operating in public-company environments with SOX, compliance, controls, governance, and audit requirements.
• Track record of influencing senior stakeholders, resolving ambiguity, driving decisions without formal authority, and building structure in a fast-scaling environment.
• Ability to maintain a hybrid presence in the Bay Area.
Core Strengths
• Enterprise systems and process thinker who can connect strategy, operating models, controls, data, and technology.
• Structured analyst who can turn ambiguous problems into clear decisions and executable work.
• Excellent facilitator and stakeholder manager who communicates across business and technology audiences, builds alignment, and constructively challenges assumptions. • Detail-oriented operator who balances delivery speed with scalability, controls, and long-term maintainability.
• Self-directed learner who adopts new technologies quickly and helps others raise their capability.
Success in This Role Looks Like
• Clear, prioritized business-systems roadmaps and backlogs aligned with enterprise strategy, functional outcomes, and BIS capacity.
• High-quality, sprint-ready requirements that reduce rework and enable predictable delivery across Architecture and Engineering.
• Simpler, better-controlled processes with measurable gains in efficiency, data quality, automation, and user experience.
• Strong system adoption, sustained business ownership, and reliable applications with fewer recurring production issues.
• Trusted partnership among business functions, BIS, vendors, and other stakeholders, supported by reusable analysis and process standards.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nScope: Enterprise business processes and systems across BIS-supported functions\n\nRole Overview\n\nWe are looking for a Staff Business Systems Analyst who can connect business strategy, process design, enterprise systems, and technology delivery across the functions supported by Business Intelligence & Systems (BIS). This role serves as a senior functional partner to business teams and translates complex needs into clear business cases, process designs, functional specifications, and sprint-ready work. The role partners closely with functional leaders, BIS Architecture, Engineering, Data, Production Support, and external vendors to deliver scalable, well-controlled, and supportable business capabilities.\n\nKey Responsibilities\n\n• Partner with the functional leaders to shape executive roadmaps, business cases, intake, prioritization, and measurable business outcomes.\n\n• Lead discovery, current-state and future-state process mapping, root-cause analysis, and gap assessment across Finance, Supply Chain and Distribution Center Operations, People and Legal, and emerging business areas as needed.\n\n• Translate business needs into functional requirements, process and data flows, user stories, acceptance criteria, product specifications, and sprint-ready backlog items.\n\n• Develop functional depth in the applications and processes within assigned domains, including ERP and other enterprise platforms, integrations, reporting, controls, and downstream data dependencies.\n\n• Facilitate cross-functional design sessions with Technical Architecture and Engineering, evaluate solution tradeoffs, drive decisions, and ensure designs align with enterprise standards, integration strategy, and long-term scalability.\n\n• Maintain requirements traceability and lead functional validation, user acceptance testing, defect triage, release readiness, training, and adoption activities.\n\n• Embed compliance, segregation-of-duties, auditability, security, data quality, and operational controls into process and system designs, particularly in a public-company environment.\n\n• Analyze production issues as needed and business-process KPIs, define durable improvements, and coordinate clear handoffs to Engineering and Production Support.\n\n• Lead or support vendor evaluations and contribute functional leadership throughout solution selection, implementation, and post-launch stabilization.\n\n• Identify practical opportunities for workflow automation and AI-enabled capabilities while maintaining appropriate controls, transparency, and business ownership.\n\n• Raise the quality of business analysis across BIS by establishing reusable standards, coaching peers, and modeling structured, outcome-oriented problem solving across multiple domains.\n\nBackground We're Looking For\n\n• Proven experience in a senior Business Systems Analyst, Business Process, Product, Program, or comparable enterprise-systems role.\n\n• Demonstrated success leading end-to-end business transformations across process, technology, data, controls, and change adoption.\n\n• Strong functional depth in one or more enterprise domains such as Finance, Supply Chain and Distribution Center Operations, People, Legal, or other corporate functions, with the ability to learn additional domains quickly.\n\n• Strong hands-on experience with enterprise applications such as ERP and adjacent business platforms; experience with integrations, analytics, reporting, and workflow automation is highly valued.\n\n• Strong command of business-analysis practices, including process modeling, requirements elicitation, functional specifications, user stories, acceptance criteria, UAT, and release readiness.\n\n• Technical fluency sufficient to work effectively with architects, engineers, integration teams, data teams, and vendors; an engineering or technical background is a plus.\n\n• Experience operating in public-company environments with SOX, compliance, controls, governance, and audit requirements.\n\n• Track record of influencing senior stakeholders, resolving ambiguity, driving decisions without formal authority, and building structure in a fast-scaling environment.\n\n• Ability to maintain a hybrid presence in the Bay Area.\n\nCore Strengths\n\n• Enterprise systems and process thinker who can connect strategy, operating models, controls, data, and technology.\n\n• Structured analyst who can turn ambiguous problems into clear decisions and executable work.\n\n• Excellent facilitator and stakeholder manager who communicates across business and technology audiences, builds alignment, and constructively challenges assumptions. • Detail-oriented operator who balances delivery speed with scalability, controls, and long-term maintainability.\n\n• Self-directed learner who adopts new technologies quickly and helps others raise their capability.\n\nSuccess in This Role Looks Like\n\n• Clear, prioritized business-systems roadmaps and backlogs aligned with enterprise strategy, functional outcomes, and BIS capacity.\n\n• High-quality, sprint-ready requirements that reduce rework and enable predictable delivery across Architecture and Engineering.\n\n• Simpler, better-controlled processes with measurable gains in efficiency, data quality, automation, and user experience.\n\n• Strong system adoption, sustained business ownership, and reliable applications with fewer recurring production issues.\n\n• Trusted partnership among business functions, BIS, vendors, and other stakeholders, supported by reusable analysis and process standards.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"156a5e00-bfc3-4a16-b7a0-57a1c3b6ac8d","title":"Sr. Operations Manager","department":"Hardware","team":"Supply Chain","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2026-08-21T18:16:49.258+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/156a5e00-bfc3-4a16-b7a0-57a1c3b6ac8d","applyUrl":"https://jobs.ashbyhq.com/cerebras/156a5e00-bfc3-4a16-b7a0-57a1c3b6ac8d/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Position Summary
The Sr. Operations Manager will lead warehouse operations, inventory control, 3PL execution, and reverse logistics inventory ownership in a fast-paced manufacturing and supply chain environment. This role connects physical material movement, warehouse readiness, partner execution, system transaction discipline, and audit-ready controls across internal warehouses, manufacturing sites, contract manufacturers, 3PLs, and partner-held inventory locations.
The role strengthens inventory accuracy, cycle count governance, warehouse scalability, SOX readiness, RMA / reverse logistics execution, and exception management. Transportation, carrier management, and freight execution remain owned by Logistics; this role owns inventory movement control, transaction accuracy, system tracking, receipt confirmation, and cross-functional coordination through final receipt.
Key Responsibilities
Inventory Control & Governance
Own the end-to-end inventory control operating model across internal warehouses, manufacturing locations, contract manufacturers, 3PLs, and partner-held inventory locations.
Set standards for ABC / risk-based counts, high-value inventory, exception approvals, and discrepancy closure.
Improve inventory practices to protect margin, reduce loss and write-offs, and strengthen perpetual accuracy.
Ensure physical inventory movements, ERP/WMS transactions, supporting documentation, approvals, and financial controls remain aligned.
Drive root-cause analysis and corrective actions for count variances, transfer discrepancies, receiving issues, RMA activity, MRB, scrap, unbuild activity, holds, aging inventory, and open exceptions.
Warehouse Footprint & Scalability
Define the warehouse and inventory footprint strategy needed to support growth, inventory accuracy, and transaction discipline.
Evaluate internal warehouse, 3PL, partner, and contract manufacturer nodes against volume, material risk, storage needs, service levels, and controls.
Partner with cross-functional leaders to develop scalable warehouse processes, storage strategies, location controls, receiving protocols, inventory movement standards, and disposition workflows.
Identify capacity risks, process gaps, and control weaknesses that may impact inventory availability, margin, production continuity, or audit readiness.
3PL Partnership & Performance
Own 3PL operating relationships, governance cadence, performance management, issue escalation, and service-level expectations.
Set standards for receiving, storage, transfers, cycle counts, shipment handoffs, POD retention, exception reporting, and transaction timing.
Partner with 3PLs to improve inventory accuracy, reduce manual reconciliation, strengthen custody controls, and ensure audit-ready evidence retention.
Monitor partner performance through KPIs, scorecards, business reviews, and corrective action plans.
RMA / Reverse Logistics Inventory
Own inventory control for RMA and reverse logistics movements to and from internal sites, manufacturing locations, contract manufacturers, 3PLs, and customer or field locations through final receipt and reconciliation.
Ensure RMA and reverse logistics movements are accurately tracked in ERP / WMS systems, including documentation, location status, custody changes, receipt confirmation, and exceptions.
Coordinate with Logistics, Warehouse, Manufacturing, Quality, Customer Support, Finance, 3PLs, and partner teams to ensure returned or transferred materials are received, inspected, dispositioned, and transacted accurately.
Logistics owns transportation execution, carrier selection, and freight management; this role owns inventory visibility, transaction accuracy, system reconciliation, and operational follow-through.
Drive closure of missing receipts, transaction gaps, aging RMA inventory, in-transit discrepancies, undocumented returns, and unresolved reverse logistics exceptions.
Finance Partnership, SOX Readiness & Audit Controls
Partner with Finance and Accounting to ensure inventory activity supports accurate valuation, period-end close, audit evidence, and SOX readiness.
Define operational controls for inventory adjustments, cycle count variances, receipts, transfers, scrap, MRB, RMA, unbuild activity, and partner-held inventory.
Maintain audit-ready documentation for custody, receiving support, count execution, adjustment approvals, inventory movement evidence, and corrective actions.
Support month-end, quarter-end, and year-end readiness by driving timely exception closure and reducing manual reconciliation burden.
Escalate control gaps, aging exceptions, missing evidence, or process noncompliance that may create financial exposure, audit risk, or inventory misstatement.
Warehouse Operations & Process Execution
Lead warehouse operating standards for receiving, put-away, storage, inventory movements, staging, kitting support, shipment handoffs, and controlled disposition workflows.
Ensure warehouse processes are scalable, documented, consistently followed, and aligned with ERP / WMS controls.
Drive daily operating discipline for transaction timing, physical-to-system alignment, location accuracy, and exception follow-up.
Partner with Warehouse, Manufacturing, Supply Chain, Quality, Engineering, Finance, and Logistics teams to resolve operational blockers and improve material flow.
Identify and implement process improvements that reduce manual effort, improve inventory visibility, strengthen custody controls, and support manufacturing continuity.
Systems, Reporting & Continuous Improvement
Partner with BIS / Systems and operational stakeholders to improve ERP / WMS workflows, reporting, dashboards, exception queues, access controls, and partner data feeds.
Use data to identify recurring defects, transaction lag, aging exceptions, partner performance issues, count variance trends, and inventory risk exposure.
Develop and monitor KPIs for inventory accuracy, cycle count completion, transaction SLA compliance, exception aging, receiving discipline, adjustment trends, and 3PL performance.
Lead corrective action planning and continuous improvement initiatives that address root causes rather than one-off cleanup.
Translate operational data into clear leadership updates, prioritization recommendations, and action plans.
Required Qualifications
8+ years of experience in warehouse operations, inventory control, supply chain operations, manufacturing operations, 3PL management, logistics operations, or a related field.
Demonstrated experience leading inventory control, warehouse execution, partner operations, cycle counts, discrepancy resolution, and operational process improvement.
Strong understanding of inventory practices, including receiving, transfers, cycle counting, variance investigation, inventory adjustments, scrap, MRB, RMA / reverse logistics movements, unbuild / rebuild activity, storage controls, transaction accuracy, and physical inventory governance.
Experience working across multiple inventory nodes such as internal warehouses, manufacturing sites, contract manufacturers, 3PLs, data centers, or external partner locations.
Working knowledge of ERP, WMS, and operational reporting systems; NetSuite experience is strongly preferred.
Ability to partner effectively with Finance and Accounting on inventory controls, audit evidence, SOX readiness, period-end close, and financial exposure related to inventory activity.
Strong analytical skills with the ability to convert operational data into root-cause insights, corrective actions, and leadership recommendations.
Excellent communication, escalation, and cross-functional leadership skills, with the ability to influence internal teams and external partners without direct authority.
Preferred Qualifications
Experience in hardware, semiconductor, electronics, data center infrastructure, contract manufacturing, or other complex technical manufacturing environments.
Experience managing 3PL operating relationships, partner scorecards, business reviews, service-level expectations, and corrective action plans.
Experience with SOX controls, audit readiness, segregation of duties, inventory valuation, or financial control environments.
Experience implementing or improving ERP / WMS processes, dashboards, inventory reporting, or systematic controls; NetSuite experience is a plus.
Bachelor’s degree in Supply Chain Management, Operations, Business, Engineering, or a related field; equivalent experience will be considered.
APICS CPIM, CSCP, Lean Six Sigma, PMP, or related certification is a plus.
Key Competencies
Operational ownership and follow-through
Strong inventory control judgment and risk prioritization
Analytical problem-solving and root-cause discipline
Ability to operate in ambiguity and build scalable processes
Cross-functional collaboration and professional conflict resolution
Clear written and verbal communication
Partner management and escalation discipline
High attention to detail, documentation, and audit evidence
Continuous improvement mindset
Success Measures
Improved inventory record accuracy across internal, contract manufacturer, partner, and 3PL locations.
Reduced cycle count variance aging, inventory adjustments, write-offs, and recurring discrepancy drivers.
Improved transaction SLA adherence for receiving, transfers, inventory movements, RMA / reverse logistics, scrap, MRB, and unbuild activity.
Improved visibility, receipt confirmation, and system transaction accuracy for materials moving to and from sites through RMA and reverse logistics workflows.
Audit-ready documentation for inventory custody, adjustments, approvals, count execution, and corrective actions.
Improved 3PL performance visibility through scorecards, recurring reviews, and timely corrective action closure.
Reduced manual reconciliation burden for Finance, Operations, and Systems teams.
The base salary range for this position is $204,000 to $299,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nPosition Summary\n\nThe Sr. Operations Manager will lead warehouse operations, inventory control, 3PL execution, and reverse logistics inventory ownership in a fast-paced manufacturing and supply chain environment. This role connects physical material movement, warehouse readiness, partner execution, system transaction discipline, and audit-ready controls across internal warehouses, manufacturing sites, contract manufacturers, 3PLs, and partner-held inventory locations.\n\nThe role strengthens inventory accuracy, cycle count governance, warehouse scalability, SOX readiness, RMA / reverse logistics execution, and exception management. Transportation, carrier management, and freight execution remain owned by Logistics; this role owns inventory movement control, transaction accuracy, system tracking, receipt confirmation, and cross-functional coordination through final receipt.\n\nKey Responsibilities\n\nInventory Control & Governance\n\n - Own the end-to-end inventory control operating model across internal warehouses, manufacturing locations, contract manufacturers, 3PLs, and partner-held inventory locations.\n\n - Set standards for ABC / risk-based counts, high-value inventory, exception approvals, and discrepancy closure.\n\n - Improve inventory practices to protect margin, reduce loss and write-offs, and strengthen perpetual accuracy.\n\n - Ensure physical inventory movements, ERP/WMS transactions, supporting documentation, approvals, and financial controls remain aligned.\n\n - Drive root-cause analysis and corrective actions for count variances, transfer discrepancies, receiving issues, RMA activity, MRB, scrap, unbuild activity, holds, aging inventory, and open exceptions.\n\nWarehouse Footprint & Scalability\n\n - Define the warehouse and inventory footprint strategy needed to support growth, inventory accuracy, and transaction discipline.\n\n - Evaluate internal warehouse, 3PL, partner, and contract manufacturer nodes against volume, material risk, storage needs, service levels, and controls.\n\n - Partner with cross-functional leaders to develop scalable warehouse processes, storage strategies, location controls, receiving protocols, inventory movement standards, and disposition workflows.\n\n - Identify capacity risks, process gaps, and control weaknesses that may impact inventory availability, margin, production continuity, or audit readiness.\n\n3PL Partnership & Performance\n\n - Own 3PL operating relationships, governance cadence, performance management, issue escalation, and service-level expectations.\n\n - Set standards for receiving, storage, transfers, cycle counts, shipment handoffs, POD retention, exception reporting, and transaction timing.\n\n - Partner with 3PLs to improve inventory accuracy, reduce manual reconciliation, strengthen custody controls, and ensure audit-ready evidence retention.\n\n - Monitor partner performance through KPIs, scorecards, business reviews, and corrective action plans.\n\nRMA / Reverse Logistics Inventory\n\n - Own inventory control for RMA and reverse logistics movements to and from internal sites, manufacturing locations, contract manufacturers, 3PLs, and customer or field locations through final receipt and reconciliation.\n\n - Ensure RMA and reverse logistics movements are accurately tracked in ERP / WMS systems, including documentation, location status, custody changes, receipt confirmation, and exceptions.\n\n - Coordinate with Logistics, Warehouse, Manufacturing, Quality, Customer Support, Finance, 3PLs, and partner teams to ensure returned or transferred materials are received, inspected, dispositioned, and transacted accurately.\n\n - Logistics owns transportation execution, carrier selection, and freight management; this role owns inventory visibility, transaction accuracy, system reconciliation, and operational follow-through.\n\n - Drive closure of missing receipts, transaction gaps, aging RMA inventory, in-transit discrepancies, undocumented returns, and unresolved reverse logistics exceptions.\n\nFinance Partnership, SOX Readiness & Audit Controls\n\n - Partner with Finance and Accounting to ensure inventory activity supports accurate valuation, period-end close, audit evidence, and SOX readiness.\n\n - Define operational controls for inventory adjustments, cycle count variances, receipts, transfers, scrap, MRB, RMA, unbuild activity, and partner-held inventory.\n\n - Maintain audit-ready documentation for custody, receiving support, count execution, adjustment approvals, inventory movement evidence, and corrective actions.\n\n - Support month-end, quarter-end, and year-end readiness by driving timely exception closure and reducing manual reconciliation burden.\n\n - Escalate control gaps, aging exceptions, missing evidence, or process noncompliance that may create financial exposure, audit risk, or inventory misstatement.\n\nWarehouse Operations & Process Execution\n\n - Lead warehouse operating standards for receiving, put-away, storage, inventory movements, staging, kitting support, shipment handoffs, and controlled disposition workflows.\n\n - Ensure warehouse processes are scalable, documented, consistently followed, and aligned with ERP / WMS controls.\n\n - Drive daily operating discipline for transaction timing, physical-to-system alignment, location accuracy, and exception follow-up.\n\n - Partner with Warehouse, Manufacturing, Supply Chain, Quality, Engineering, Finance, and Logistics teams to resolve operational blockers and improve material flow.\n\n - Identify and implement process improvements that reduce manual effort, improve inventory visibility, strengthen custody controls, and support manufacturing continuity.\n\nSystems, Reporting & Continuous Improvement\n\n - Partner with BIS / Systems and operational stakeholders to improve ERP / WMS workflows, reporting, dashboards, exception queues, access controls, and partner data feeds.\n\n - Use data to identify recurring defects, transaction lag, aging exceptions, partner performance issues, count variance trends, and inventory risk exposure.\n\n - Develop and monitor KPIs for inventory accuracy, cycle count completion, transaction SLA compliance, exception aging, receiving discipline, adjustment trends, and 3PL performance.\n\n - Lead corrective action planning and continuous improvement initiatives that address root causes rather than one-off cleanup.\n\n - Translate operational data into clear leadership updates, prioritization recommendations, and action plans.\n\nRequired Qualifications\n\n - 8+ years of experience in warehouse operations, inventory control, supply chain operations, manufacturing operations, 3PL management, logistics operations, or a related field.\n\n - Demonstrated experience leading inventory control, warehouse execution, partner operations, cycle counts, discrepancy resolution, and operational process improvement.\n\n - Strong understanding of inventory practices, including receiving, transfers, cycle counting, variance investigation, inventory adjustments, scrap, MRB, RMA / reverse logistics movements, unbuild / rebuild activity, storage controls, transaction accuracy, and physical inventory governance.\n\n - Experience working across multiple inventory nodes such as internal warehouses, manufacturing sites, contract manufacturers, 3PLs, data centers, or external partner locations.\n\n - Working knowledge of ERP, WMS, and operational reporting systems; NetSuite experience is strongly preferred.\n\n - Ability to partner effectively with Finance and Accounting on inventory controls, audit evidence, SOX readiness, period-end close, and financial exposure related to inventory activity.\n\n - Strong analytical skills with the ability to convert operational data into root-cause insights, corrective actions, and leadership recommendations.\n\n - Excellent communication, escalation, and cross-functional leadership skills, with the ability to influence internal teams and external partners without direct authority.\n\nPreferred Qualifications\n\n - Experience in hardware, semiconductor, electronics, data center infrastructure, contract manufacturing, or other complex technical manufacturing environments.\n\n - Experience managing 3PL operating relationships, partner scorecards, business reviews, service-level expectations, and corrective action plans.\n\n - Experience with SOX controls, audit readiness, segregation of duties, inventory valuation, or financial control environments.\n\n - Experience implementing or improving ERP / WMS processes, dashboards, inventory reporting, or systematic controls; NetSuite experience is a plus.\n\n - Bachelor’s degree in Supply Chain Management, Operations, Business, Engineering, or a related field; equivalent experience will be considered.\n\n - APICS CPIM, CSCP, Lean Six Sigma, PMP, or related certification is a plus.\n\nKey Competencies\n\n - Operational ownership and follow-through\n\n - Strong inventory control judgment and risk prioritization\n\n - Analytical problem-solving and root-cause discipline\n\n - Ability to operate in ambiguity and build scalable processes\n\n - Cross-functional collaboration and professional conflict resolution\n\n - Clear written and verbal communication\n\n - Partner management and escalation discipline\n\n - High attention to detail, documentation, and audit evidence\n\n - Continuous improvement mindset\n\nSuccess Measures\n\n - Improved inventory record accuracy across internal, contract manufacturer, partner, and 3PL locations.\n\n - Reduced cycle count variance aging, inventory adjustments, write-offs, and recurring discrepancy drivers.\n\n - Improved transaction SLA adherence for receiving, transfers, inventory movements, RMA / reverse logistics, scrap, MRB, and unbuild activity.\n\n - Improved visibility, receipt confirmation, and system transaction accuracy for materials moving to and from sites through RMA and reverse logistics workflows.\n\n - Audit-ready documentation for inventory custody, adjustments, approvals, count execution, and corrective actions.\n\n - Improved 3PL performance visibility through scorecards, recurring reviews, and timely corrective action closure.\n\n - Reduced manual reconciliation burden for Finance, Operations, and Systems teams.\n\n\n\nThe base salary range for this position is $204,000 to $299,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.\n\n\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"5ec9197f-2534-414b-88f6-9d13563c8157","title":"Technical Program Manager, Manufacturing Test","department":"Hardware","team":"Manufacturing","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2026-08-26T04:53:41.055+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California ","addressCountry":"United States","addressLocality":"Sunnyvale "}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/5ec9197f-2534-414b-88f6-9d13563c8157","applyUrl":"https://jobs.ashbyhq.com/cerebras/5ec9197f-2534-414b-88f6-9d13563c8157/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Technical Program Manager, Manufacturing Test
Team: Manufacturing Test Engineering | Location: Sunnyvale, CA, with occasional travel to manufacturing partners.
About the role
We build the hardware behind frontier AI, and getting it into volume production reliably is a team sport. We're looking for a Technical Program Manager to drive our manufacturing test programs - the hardware and software used to test our products at the board, sub-module, and system level - from new product introduction (NPI) through to full production. You'll be the connective tissue between engineering and the factory, turning new test capabilities into qualified, repeatable, high-volume production flows and keeping them on schedule as we ramp.
What you'll do
Own manufacturing test programs end-to-end -from NPI through qualification, production ramp, and sustaining -for test hardware and software across board, sub-module, and system-level testing.
Build and drive the plan -milestones, dependencies, critical path, and clear entry/exit gates -and keep it on track as priorities shift.
Coordinate across teams -test, hardware, and software engineering, manufacturing operations, quality, and external manufacturing partners.
Work hand-in-hand with program-level TPMs rolling up test readiness, risks, and dependencies into the broader product programs.
Manage risk proactively -maintain a living risk register, surface issues early, and drive them to closure with clear owners and dates.
Own the qualification-to-production handoff -ensure test changes are validated, controlled, and cleanly promoted before they reach the line.
Run the operating cadence -reviews, status reporting, and metrics (yield, test time, throughput, capacity) that drive decisions.
Plan for scale -keep test capacity and readiness ahead of the production ramp.
What you have (Minimum qualifications)
Bachelor's degree in engineering, a related technical field, or equivalent practical experience.
3+ years of technical program or project management experience in a hardware, electronics, or semiconductor manufacturing environment.
Demonstrated success driving cross-functional programs to a schedule, including with teams that don't report to you.
Working knowledge of manufacturing test and/or the NPI-to-production lifecycle.
Enough technical fluency across test hardware and software to earn engineers' trust and make sound trade-offs.
Clear, data-driven communication with both technical and leadership audiences.
Nice to have (Preferred qualifications)
Experience with contract manufacturers or across multiple sites.
Exposure to test development, automation, or manufacturing execution systems (MES).
Familiarity with quality and change-control practices in a high-reliability environment.
PMP, Six Sigma, or equivalent.
Why join
You'll have real ownership of programs that put first-of-their-kind hardware into production, working alongside a deeply technical team on problems that don't have a playbook yet.
We're an equal-opportunity employer and value a diverse, inclusive workplace. We encourage you to apply even if your experience doesn't line up perfectly.
The base salary range for this position is $150,000 to $220,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nTechnical Program Manager, Manufacturing Test\n\nTeam: Manufacturing Test Engineering | Location: Sunnyvale, CA, with occasional travel to manufacturing partners.\n\nAbout the role\n\nWe build the hardware behind frontier AI, and getting it into volume production reliably is a team sport. We're looking for a Technical Program Manager to drive our manufacturing test programs - the hardware and software used to test our products at the board, sub-module, and system level - from new product introduction (NPI) through to full production. You'll be the connective tissue between engineering and the factory, turning new test capabilities into qualified, repeatable, high-volume production flows and keeping them on schedule as we ramp.\n\nWhat you'll do\n\n - Own manufacturing test programs end-to-end -from NPI through qualification, production ramp, and sustaining -for test hardware and software across board, sub-module, and system-level testing.\n\n - Build and drive the plan -milestones, dependencies, critical path, and clear entry/exit gates -and keep it on track as priorities shift.\n\n - Coordinate across teams -test, hardware, and software engineering, manufacturing operations, quality, and external manufacturing partners.\n\n - Work hand-in-hand with program-level TPMs rolling up test readiness, risks, and dependencies into the broader product programs.\n\n - Manage risk proactively -maintain a living risk register, surface issues early, and drive them to closure with clear owners and dates.\n\n - Own the qualification-to-production handoff -ensure test changes are validated, controlled, and cleanly promoted before they reach the line.\n\n - Run the operating cadence -reviews, status reporting, and metrics (yield, test time, throughput, capacity) that drive decisions.\n\n - Plan for scale -keep test capacity and readiness ahead of the production ramp.\n\nWhat you have (Minimum qualifications)\n\n - Bachelor's degree in engineering, a related technical field, or equivalent practical experience.\n\n - 3+ years of technical program or project management experience in a hardware, electronics, or semiconductor manufacturing environment.\n\n - Demonstrated success driving cross-functional programs to a schedule, including with teams that don't report to you.\n\n - Working knowledge of manufacturing test and/or the NPI-to-production lifecycle.\n\n - Enough technical fluency across test hardware and software to earn engineers' trust and make sound trade-offs.\n\n - Clear, data-driven communication with both technical and leadership audiences.\n\nNice to have (Preferred qualifications)\n\n - Experience with contract manufacturers or across multiple sites.\n\n - Exposure to test development, automation, or manufacturing execution systems (MES).\n\n - Familiarity with quality and change-control practices in a high-reliability environment.\n\n - PMP, Six Sigma, or equivalent.\n\nWhy join\n\nYou'll have real ownership of programs that put first-of-their-kind hardware into production, working alongside a deeply technical team on problems that don't have a playbook yet.\n\nWe're an equal-opportunity employer and value a diverse, inclusive workplace. We encourage you to apply even if your experience doesn't line up perfectly.\n\nThe base salary range for this position is $150,000 to $220,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"d67609c3-6604-487e-8482-2ceffdb3f288","title":"Senior Supplier Quality Engineer","department":"Hardware","team":"Quality & Reliability","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2026-08-28T05:33:49.486+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressRegion":"California ","addressCountry":"United States","addressLocality":"Sunnyvale "}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/d67609c3-6604-487e-8482-2ceffdb3f288","applyUrl":"https://jobs.ashbyhq.com/cerebras/d67609c3-6604-487e-8482-2ceffdb3f288/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About the Role
We are looking for a hands-on Senior Supplier Quality Engineer to lead supplier qualification and quality performance for components, printed circuit board assemblies (PCBAs), subassemblies, and system-level products. This role is responsible for ensuring that new and existing suppliers have capable processes, effective quality systems, and the controls required to consistently meet technical, quality, delivery, and reliability expectations.
The ideal candidate brings deep expertise in supplier assessment, quality-system and process auditing, First Article Inspection (FAI), supplier corrective action, and manufacturing quality methods. Working closely with Strategic Sourcing, Design Engineering, Manufacturing Engineering, Reliability Engineering, Operations, and suppliers, you will identify and reduce supplier risk throughout the product lifecycle.
The primary focus of this role is assessing and qualifying new suppliers, approving new parts and processes, monitoring supplier performance, and driving timely containment and permanent corrective action when requirements are not met.
Supplier Assessment and Qualification
• Lead the end-to-end assessment and qualification of new suppliers, including technical capability, quality systems, manufacturing controls, capacity, traceability, and overall risk.
• Plan and conduct supplier quality-system and process audits; document findings, assess risk, and drive corrective actions to closure before approval.
• Evaluate supplier process capability, special-process controls, inspection and test methods, calibration, sub-tier management, and change-control practices.
• Partner with Strategic Sourcing and Engineering to define qualification requirements, select suppliers, and make evidence-based approval decisions.
• Maintain supplier qualification records, audit results, risk ratings, and approved supplier status; establish surveillance or development plans when gaps remain.
NPI Supplier Readiness and First Article Approval
• Define supplier quality deliverables for new parts and NPI builds, including quality plans, inspection requirements, control plans, and production-readiness criteria.
• Review and approve First Article Inspection packages for completeness and compliance, including drawings, dimensional results, material and process certifications, and objective evidence.
• Drive APQP and PPAP activities where applicable, including PFMEA, process flow, control plans, MSA, capability studies, and validation of critical-to-quality characteristics.
• Verify supplier production readiness through on-site reviews, pilot-build support, and closure of open risks before release to volume production.
Supplier Performance and Quality Execution
• Serve as the primary quality interface for assigned suppliers and commodities, setting clear expectations, escalation paths, and accountability for quality performance.
• Monitor supplier scorecards and quality trends, including defect rates, PPM, escapes, on-time corrective action, audit findings, and repeat nonconformances.
• Establish risk-based incoming inspection and supplier surveillance plans; reduce inspection only after sustained evidence of process capability and performance.
• Support nonconformance disposition, deviations, material review, supplier change notifications, and qualification of process, tooling, site, or sub-tier changes.
SCAR and Corrective Action Leadership
• Issue and manage Supplier Corrective Action Requests (SCARs), ensuring rapid containment, clear problem definition, protected production, and disciplined execution according to agreed timelines.
• Lead and coach suppliers through rigorous root-cause analysis using 8D, 5 Whys, fishbone analysis, fault-tree analysis, and other appropriate methods; reject unsupported or symptom-based conclusions.
• Validate root causes, approve corrective and preventive actions, verify effectiveness with objective evidence, and drive systemic improvements that prevent recurrence across similar parts and processes.
Skills and Qualifications
• Bachelor’s degree in Engineering and 7–10+ years of Supplier Quality, Quality Engineering, or Manufacturing Quality experience supporting complex hardware products.
• Demonstrated experience assessing, auditing, qualifying, and developing suppliers across electronics, electromechanical, and mechanical commodities.
• Strong knowledge of quality-management systems and supplier auditing against ISO 9001, AS9100, or other applicable industry standards; lead-auditor or quality certification preferred.
• Hands-on experience reviewing First Article Inspection and APQP/PPAP deliverables, including drawings, GD&T, dimensional reports, material certifications, PFMEAs, control plans, MSA, and capability data.
• Proven success managing SCARs and leading supplier root-cause investigations and corrective actions using 8D, 5 Whys, and related methodologies.
• Strong understanding of manufacturing and inspection processes for relevant commodities, such as PCBAs, cables, sheet metal, machined parts, plastics, and system assemblies.
• Strong working knowledge of SPC, Cp/Cpk, MSA, sampling plans, control plans, PFMEA, and risk-based supplier quality controls.
• Ability to interpret engineering drawings and specifications, distinguish evidence from assumptions, and communicate technical quality risks clearly across suppliers and cross-functional teams.
• Demonstrated knowledge of Product Lifecycle Management (PLM) systems and best practices, including part and document control, revision and change management, approval workflows, supplier data, and configuration traceability.
• Willingness to travel to domestic and international supplier sites for qualification, audits, production readiness, issue resolution, and supplier development.
The base salary range for this position is $175,000 to $275,000 annually. Actual compensation may include bonus and equity and will be determined based on factors such as experience, skills, and qualifications.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout the Role\n\nWe are looking for a hands-on Senior Supplier Quality Engineer to lead supplier qualification and quality performance for components, printed circuit board assemblies (PCBAs), subassemblies, and system-level products. This role is responsible for ensuring that new and existing suppliers have capable processes, effective quality systems, and the controls required to consistently meet technical, quality, delivery, and reliability expectations.\n\nThe ideal candidate brings deep expertise in supplier assessment, quality-system and process auditing, First Article Inspection (FAI), supplier corrective action, and manufacturing quality methods. Working closely with Strategic Sourcing, Design Engineering, Manufacturing Engineering, Reliability Engineering, Operations, and suppliers, you will identify and reduce supplier risk throughout the product lifecycle.\n\nThe primary focus of this role is assessing and qualifying new suppliers, approving new parts and processes, monitoring supplier performance, and driving timely containment and permanent corrective action when requirements are not met.\n\n\n\n\n\nSupplier Assessment and Qualification\n\n• Lead the end-to-end assessment and qualification of new suppliers, including technical capability, quality systems, manufacturing controls, capacity, traceability, and overall risk.\n\n• Plan and conduct supplier quality-system and process audits; document findings, assess risk, and drive corrective actions to closure before approval.\n\n• Evaluate supplier process capability, special-process controls, inspection and test methods, calibration, sub-tier management, and change-control practices.\n\n• Partner with Strategic Sourcing and Engineering to define qualification requirements, select suppliers, and make evidence-based approval decisions.\n\n• Maintain supplier qualification records, audit results, risk ratings, and approved supplier status; establish surveillance or development plans when gaps remain.\n\n\n\n\n\nNPI Supplier Readiness and First Article Approval\n\n• Define supplier quality deliverables for new parts and NPI builds, including quality plans, inspection requirements, control plans, and production-readiness criteria.\n\n• Review and approve First Article Inspection packages for completeness and compliance, including drawings, dimensional results, material and process certifications, and objective evidence.\n\n• Drive APQP and PPAP activities where applicable, including PFMEA, process flow, control plans, MSA, capability studies, and validation of critical-to-quality characteristics.\n\n• Verify supplier production readiness through on-site reviews, pilot-build support, and closure of open risks before release to volume production.\n\n\n\n\n\nSupplier Performance and Quality Execution\n\n• Serve as the primary quality interface for assigned suppliers and commodities, setting clear expectations, escalation paths, and accountability for quality performance.\n\n• Monitor supplier scorecards and quality trends, including defect rates, PPM, escapes, on-time corrective action, audit findings, and repeat nonconformances.\n\n• Establish risk-based incoming inspection and supplier surveillance plans; reduce inspection only after sustained evidence of process capability and performance.\n\n• Support nonconformance disposition, deviations, material review, supplier change notifications, and qualification of process, tooling, site, or sub-tier changes.\n\n\n\n\n\nSCAR and Corrective Action Leadership\n\n• Issue and manage Supplier Corrective Action Requests (SCARs), ensuring rapid containment, clear problem definition, protected production, and disciplined execution according to agreed timelines.\n\n• Lead and coach suppliers through rigorous root-cause analysis using 8D, 5 Whys, fishbone analysis, fault-tree analysis, and other appropriate methods; reject unsupported or symptom-based conclusions.\n\n• Validate root causes, approve corrective and preventive actions, verify effectiveness with objective evidence, and drive systemic improvements that prevent recurrence across similar parts and processes.\n\n\n\n\n\nSkills and Qualifications\n\n• Bachelor’s degree in Engineering and 7–10+ years of Supplier Quality, Quality Engineering, or Manufacturing Quality experience supporting complex hardware products.\n\n• Demonstrated experience assessing, auditing, qualifying, and developing suppliers across electronics, electromechanical, and mechanical commodities.\n\n• Strong knowledge of quality-management systems and supplier auditing against ISO 9001, AS9100, or other applicable industry standards; lead-auditor or quality certification preferred.\n\n• Hands-on experience reviewing First Article Inspection and APQP/PPAP deliverables, including drawings, GD&T, dimensional reports, material certifications, PFMEAs, control plans, MSA, and capability data.\n\n• Proven success managing SCARs and leading supplier root-cause investigations and corrective actions using 8D, 5 Whys, and related methodologies.\n\n• Strong understanding of manufacturing and inspection processes for relevant commodities, such as PCBAs, cables, sheet metal, machined parts, plastics, and system assemblies.\n\n• Strong working knowledge of SPC, Cp/Cpk, MSA, sampling plans, control plans, PFMEA, and risk-based supplier quality controls.\n\n• Ability to interpret engineering drawings and specifications, distinguish evidence from assumptions, and communicate technical quality risks clearly across suppliers and cross-functional teams.\n\n• Demonstrated knowledge of Product Lifecycle Management (PLM) systems and best practices, including part and document control, revision and change management, approval workflows, supplier data, and configuration traceability.\n\n• Willingness to travel to domestic and international supplier sites for qualification, audits, production readiness, issue resolution, and supplier development.\n\nThe base salary range for this position is $175,000 to $275,000 annually. Actual compensation may include bonus and equity and will be determined based on factors such as experience, skills, and qualifications.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"d00a69be-436a-4926-964e-1d7f9ce75bb5","title":"VP Legal, Strategic Transactions","department":"Corporate","team":"Legal","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2026-08-29T00:38:26.625+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressRegion":"California ","addressCountry":"United States","addressLocality":"Sunnyvale "}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/d00a69be-436a-4926-964e-1d7f9ce75bb5","applyUrl":"https://jobs.ashbyhq.com/cerebras/d00a69be-436a-4926-964e-1d7f9ce75bb5/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About the Role
Cerebras has built a breakthrough architecture that is unlocking new opportunities for the AI industry. Following its IPO, Cerebras is focused on scaling its infrastructure to bring its ultra-fast compute to all users. As VP Legal, Strategic Transactions, you will quarterback and drive to close a variety of deals to scale our business and operations, including M&A, strategic investments, asset acquisitions, digital infrastructure and data center real estate transactions, and related equity and debt financings. You will also handle corporate structuring matters relating to such transactions. You will work closely with a fast-paced finance and infrastructure acquisition team, and advise the company’s c-suite on our largest and most impactful transactions.
Responsibilities
· Own end-to-end legal strategy and execution on a variety of corporate transactions, including M&A, strategic investments, asset acquisitions and real estate transactions, including a focus on data center procurement and financing.
· Drive corporate organization and structuring, including foreign expansion, in support of acquisition activity.
· Manage a variety of outside counsel relationships.
· Collaborate cross-functionally to manage interdependencies and risk across customer and vendor relationships.
Skills & Qualifications
· 12-18 years of direct experience with M&A, strategic investments, equity and debt transactions, asset purchases, and other types of complex corporate transactions.
· Demonstrated track record of quarterbacking sophisticated, high-complexity and cross-functional deals.
· Ability and desire to learn different types of transactions, including real estate and data center transactions.
· Ability to distill complex legal issues into plain English, and translate technical concepts into legal agreements.
· Fluency with due diligence, regulatory issues and dispute resolution.
· Strong ability to quickly learn other practice areas, and agility and desire to work in a fast-paced environment where the scope of work is constantly changing.
· Can-do attitude and strong work ethic; no task is beneath you and no problem is unsolvable.
· Juris Doctor (J.D.) and bar admission required.
· A mix of leading law firm and in-house experience required.
The compensation range for this position will depend on the candidate’s level of experience, and will include a bonus and significant equity.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout the Role\n\nCerebras has built a breakthrough architecture that is unlocking new opportunities for the AI industry. Following its IPO, Cerebras is focused on scaling its infrastructure to bring its ultra-fast compute to all users. As VP Legal, Strategic Transactions, you will quarterback and drive to close a variety of deals to scale our business and operations, including M&A, strategic investments, asset acquisitions, digital infrastructure and data center real estate transactions, and related equity and debt financings. You will also handle corporate structuring matters relating to such transactions. You will work closely with a fast-paced finance and infrastructure acquisition team, and advise the company’s c-suite on our largest and most impactful transactions.\n\nResponsibilities\n\n· Own end-to-end legal strategy and execution on a variety of corporate transactions, including M&A, strategic investments, asset acquisitions and real estate transactions, including a focus on data center procurement and financing.\n\n· Drive corporate organization and structuring, including foreign expansion, in support of acquisition activity.\n\n· Manage a variety of outside counsel relationships.\n\n· Collaborate cross-functionally to manage interdependencies and risk across customer and vendor relationships.\n\nSkills & Qualifications\n\n· 12-18 years of direct experience with M&A, strategic investments, equity and debt transactions, asset purchases, and other types of complex corporate transactions.\n\n· Demonstrated track record of quarterbacking sophisticated, high-complexity and cross-functional deals.\n\n· Ability and desire to learn different types of transactions, including real estate and data center transactions.\n\n· Ability to distill complex legal issues into plain English, and translate technical concepts into legal agreements.\n\n· Fluency with due diligence, regulatory issues and dispute resolution.\n\n· Strong ability to quickly learn other practice areas, and agility and desire to work in a fast-paced environment where the scope of work is constantly changing.\n\n· Can-do attitude and strong work ethic; no task is beneath you and no problem is unsolvable.\n\n· Juris Doctor (J.D.) and bar admission required.\n\n· A mix of leading law firm and in-house experience required.\n\nThe compensation range for this position will depend on the candidate’s level of experience, and will include a bonus and significant equity.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"91bc61c1-29db-4a47-817d-30e921064af5","title":"Application Security Engineer","department":"IT & Security","team":"Security","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2026-09-02T12:21:41.067+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressRegion":"California ","addressCountry":"United States","addressLocality":"Sunnyvale "}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/91bc61c1-29db-4a47-817d-30e921064af5","applyUrl":"https://jobs.ashbyhq.com/cerebras/91bc61c1-29db-4a47-817d-30e921064af5/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
We are looking for an Application Security Engineer with a strong focus on Vulnerability Management to help secure Cerebras software, infrastructure, and AI platforms.
You will own and evolve key parts of our vulnerability management program from vulnerability discovery and risk prioritization through remediation and verification. This is not a ticket-management role. We are looking for an engineer who can understand vulnerabilities in context, work directly with engineering teams, automate repetitive security work, and help eliminate classes of vulnerabilities rather than simply track individual findings.
You will work closely with Engineering, Infrastructure, and IT teams to identify vulnerabilities across our products and environments and drive them to meaningful remediation.
Own and continuously improve vulnerability management across applications, software dependencies, containers, operating systems, cloud infrastructure, and externally exposed services.
Use AI agents and advanced security models to augment vulnerability discovery, code analysis, adversarial testing, prioritization, and remediation.
Analyze vulnerabilities beyond scanner severity by considering exploitability, exposure, affected assets, available mitigations, and business impact.
Partner directly with engineering teams to triage findings, determine appropriate remediation, and drive vulnerabilities to closure within risk-based SLAs.
Build automation for vulnerability ingestion, deduplication, enrichment, prioritization, assignment, remediation tracking, and reporting.
Identify systemic vulnerability patterns and work with engineering teams to address root causes rather than repeatedly fixing individual findings.
Operate and improve application security capabilities including SAST, SCA, secrets detection, container scanning, infrastructure scanning, and external attack-surface monitoring.
Validate security findings through technical investigation and hands-on testing, distinguishing exploitable vulnerabilities from false positives and low-risk findings.
Perform targeted application security reviews and testing for high-risk services and features.
Help integrate security controls into CI/CD and developer workflows while minimizing unnecessary friction for engineering teams.
Develop metrics and reporting that provide meaningful visibility into vulnerability exposure, remediation performance, recurring vulnerability classes, and security risk.
Evaluate and integrate new security technologies as our software and infrastructure environments evolve.
Partner with security and engineering teams on incident response when vulnerabilities are actively exploited or require urgent remediation.
We are looking for candidates who:
Have strong application security or product security fundamentals and hands-on experience with vulnerability management.
Understand common vulnerability classes and exploitation techniques across web applications, APIs, authentication systems, cloud services, containers, and software supply chains.
Can read and reason about code and work effectively with software engineers on practical remediation.
Have experience with vulnerability scanning and application security technologies such as SAST, SCA, DAST, secrets scanning, container scanning, or CSPM.
Understand vulnerability prioritization concepts including CVSS, exploitability, asset criticality, internet exposure, compensating controls, and threat intelligence.
Are comfortable investigating security findings manually rather than relying exclusively on scanner output.
Can automate security workflows using languages such as Python, Go, or similar scripting/programming languages.
Have experience integrating security tooling into CI/CD and modern software development workflows.
Are comfortable working with Linux, Git, containers, and cloud environments.
Can communicate security risk clearly to both security specialists and engineering teams.
Approach security with an automation-first mindset and look for scalable solutions instead of manual processes.
Experience in one or more of the following areas is a plus:
Application Security or Security engineering background.
Securing AI/ML platforms, inference services, or large-scale compute infrastructure.
Building or operating vulnerability management programs at scale.
AWS, Kubernetes, Docker, and cloud-native environments.
Software supply-chain security and dependency management.
GitHub and CI/CD security.
Threat modeling and secure design reviews.
Penetration testing or offensive security.
External attack-surface management.
Vulnerability research or exploit validation.
Security data pipelines, APIs, and workflow automation.
Using LLMs, AI agents, or AI-assisted security tooling for vulnerability research, code analysis, penetration testing, or remediation.
You will help Cerebras move beyond simply finding vulnerabilities toward an engineering-driven vulnerability management program where:
The vulnerabilities that create the most meaningful risk are identified and prioritized quickly.
Engineering teams receive actionable findings with clear remediation guidance.
High-risk vulnerabilities are consistently remediated within defined SLAs.
Security findings are increasingly validated, prioritized, and routed automatically.
Recurring vulnerability classes are addressed systematically.
AI and automation reduce manual security work and accelerate both vulnerability discovery and remediation.
Most importantly, you will help build security processes that scale with the speed at which Cerebras builds and deploys some of the most advanced AI systems in the world.ADD DESCRIPTION HERE
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nWe are looking for an Application Security Engineer with a strong focus on Vulnerability Management to help secure Cerebras software, infrastructure, and AI platforms.\n\nYou will own and evolve key parts of our vulnerability management program from vulnerability discovery and risk prioritization through remediation and verification. This is not a ticket-management role. We are looking for an engineer who can understand vulnerabilities in context, work directly with engineering teams, automate repetitive security work, and help eliminate classes of vulnerabilities rather than simply track individual findings.\n\nYou will work closely with Engineering, Infrastructure, and IT teams to identify vulnerabilities across our products and environments and drive them to meaningful remediation.\n\n\nRESPONSIBILITIES\n\n - Own and continuously improve vulnerability management across applications, software dependencies, containers, operating systems, cloud infrastructure, and externally exposed services.\n\n - Use AI agents and advanced security models to augment vulnerability discovery, code analysis, adversarial testing, prioritization, and remediation.\n\n - Analyze vulnerabilities beyond scanner severity by considering exploitability, exposure, affected assets, available mitigations, and business impact.\n\n - Partner directly with engineering teams to triage findings, determine appropriate remediation, and drive vulnerabilities to closure within risk-based SLAs.\n\n - Build automation for vulnerability ingestion, deduplication, enrichment, prioritization, assignment, remediation tracking, and reporting.\n\n - Identify systemic vulnerability patterns and work with engineering teams to address root causes rather than repeatedly fixing individual findings.\n\n - Operate and improve application security capabilities including SAST, SCA, secrets detection, container scanning, infrastructure scanning, and external attack-surface monitoring.\n\n - Validate security findings through technical investigation and hands-on testing, distinguishing exploitable vulnerabilities from false positives and low-risk findings.\n\n - Perform targeted application security reviews and testing for high-risk services and features.\n\n - Help integrate security controls into CI/CD and developer workflows while minimizing unnecessary friction for engineering teams.\n\n - Develop metrics and reporting that provide meaningful visibility into vulnerability exposure, remediation performance, recurring vulnerability classes, and security risk.\n\n - Evaluate and integrate new security technologies as our software and infrastructure environments evolve.\n\n - Partner with security and engineering teams on incident response when vulnerabilities are actively exploited or require urgent remediation.\n\n\nSKILLS & QUALIFICATIONS\n\nWe are looking for candidates who:\n\n - Have strong application security or product security fundamentals and hands-on experience with vulnerability management.\n\n - Understand common vulnerability classes and exploitation techniques across web applications, APIs, authentication systems, cloud services, containers, and software supply chains.\n\n - Can read and reason about code and work effectively with software engineers on practical remediation.\n\n - Have experience with vulnerability scanning and application security technologies such as SAST, SCA, DAST, secrets scanning, container scanning, or CSPM.\n\n - Understand vulnerability prioritization concepts including CVSS, exploitability, asset criticality, internet exposure, compensating controls, and threat intelligence.\n\n - Are comfortable investigating security findings manually rather than relying exclusively on scanner output.\n\n - Can automate security workflows using languages such as Python, Go, or similar scripting/programming languages.\n\n - Have experience integrating security tooling into CI/CD and modern software development workflows.\n\n - Are comfortable working with Linux, Git, containers, and cloud environments.\n\n - Can communicate security risk clearly to both security specialists and engineering teams.\n\n - Approach security with an automation-first mindset and look for scalable solutions instead of manual processes.\n\n\nPREFERRED QUALIFICATIONS\n\nExperience in one or more of the following areas is a plus:\n\n - Application Security or Security engineering background.\n\n - Securing AI/ML platforms, inference services, or large-scale compute infrastructure.\n\n - Building or operating vulnerability management programs at scale.\n\n - AWS, Kubernetes, Docker, and cloud-native environments.\n\n - Software supply-chain security and dependency management.\n\n - GitHub and CI/CD security.\n\n - Threat modeling and secure design reviews.\n\n - Penetration testing or offensive security.\n\n - External attack-surface management.\n\n - Vulnerability research or exploit validation.\n\n - Security data pipelines, APIs, and workflow automation.\n\n - Using LLMs, AI agents, or AI-assisted security tooling for vulnerability research, code analysis, penetration testing, or remediation.\n\n\nWHAT SUCCESS LOOKS LIKE\n\nYou will help Cerebras move beyond simply finding vulnerabilities toward an engineering-driven vulnerability management program where:\n\n - The vulnerabilities that create the most meaningful risk are identified and prioritized quickly.\n\n - Engineering teams receive actionable findings with clear remediation guidance.\n\n - High-risk vulnerabilities are consistently remediated within defined SLAs.\n\n - Security findings are increasingly validated, prioritized, and routed automatically.\n\n - Recurring vulnerability classes are addressed systematically.\n\n - AI and automation reduce manual security work and accelerate both vulnerability discovery and remediation.\n\nMost importantly, you will help build security processes that scale with the speed at which Cerebras builds and deploys some of the most advanced AI systems in the world.ADD DESCRIPTION HERE\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"bc6bb81e-6ade-49a7-b76e-5123d87bcbba","title":"Staff Software Engineer - Tools & Infrastructure / DevOps","department":"Software Engineering ","team":"Developer Productivity","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[{"location":"Toronto, CAN","address":{"postalAddress":{"addressRegion":"Ontario ","addressCountry":"Canada","addressLocality":"Toronto "}}}],"publishedAt":"2026-09-01T18:54:23.580+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressRegion":"California ","addressCountry":"United States","addressLocality":"Sunnyvale "}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/bc6bb81e-6ade-49a7-b76e-5123d87bcbba","applyUrl":"https://jobs.ashbyhq.com/cerebras/bc6bb81e-6ade-49a7-b76e-5123d87bcbba/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Responsibilities:
Design, build, and evolve CI/CD pipelines that support reliable and efficient build, test, and release workflows across the organization.
Own and improve artifact lifecycle systems, including versioning, storage, distribution, dependency management, and reproducible builds at scale.
Partner with development teams to design and improve code review workflows, branching strategies, and automated integration processes.
Provision, monitor, and optimize cloud infrastructure supporting CI workloads, balancing cost, performance, scalability, and reliability.
Troubleshoot complex build failures, pipeline bottlenecks, and infrastructure issues, driving root-cause analysis and implementing durable fixes.
Design and drive improvements to internal build infrastructure, test infrastructure, developer tooling, and automation that increase developer velocity and engineering productivity.
Identify systemic bottlenecks across developer workflows and lead architectural improvements to developer infrastructure.
Contribute to the company’s efforts around AI tooling to improve engineering productivity and automate repetitive workflows.
Provide technical leadership across projects, influence engineering standards, and mentor other engineers within the Developer Productivity organization.
Participate in on-call and incident response for Developer Productivity systems and services.
Skills & Qualifications
7+ years of professional experience in software engineering, infrastructure engineering, DevOps, developer productivity, or a related area.
Deep hands-on experience with CI/CD systems and building or evolving automated build, test, and deployment infrastructure.
Experience with artifact repositories, software packaging, dependency management, and reproducible build concepts.
Experience with cloud computing platforms, with AWS preferred, and programmatic infrastructure provisioning.
Strong experience with distributed version control systems, code review workflows, branching strategies, and repository management.
Strong understanding of Linux/Unix systems, networking fundamentals, and scripting or programming for automation.
Experience with containerization and container orchestration, with Kubernetes preferred.
Strong troubleshooting skills and the ability to debug complex distributed systems and infrastructure issues.
Demonstrated experience leading technical initiatives across multiple teams and driving improvements to developer infrastructure at organizational scale.
Ability to identify architectural bottlenecks, evaluate tradeoffs, and drive long-term improvements rather than only addressing operational issues.
Experience operating production systems and participating in on-call, incident response, and postmortem processes.
Preferred Skills & Qualifications
Experience with infrastructure-as-code tools and practices.
Proficiency in Python, Go, Shell, or another language used for infrastructure automation and developer tooling.
Experience with build systems, build graph optimization, or large-scale build infrastructure.
Experience with observability practices including monitoring, logging, alerting, and performance analysis.
Experience building internal developer platforms, self-service tooling, or developer-facing infrastructure.
Experience applying AI/LLM tooling to engineering workflows or developer productivity.
BS/MS in Computer Science or a related field, or equivalent practical experience.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nResponsibilities:\n\n - Design, build, and evolve CI/CD pipelines that support reliable and efficient build, test, and release workflows across the organization.\n\n - Own and improve artifact lifecycle systems, including versioning, storage, distribution, dependency management, and reproducible builds at scale.\n\n - Partner with development teams to design and improve code review workflows, branching strategies, and automated integration processes.\n\n - Provision, monitor, and optimize cloud infrastructure supporting CI workloads, balancing cost, performance, scalability, and reliability.\n\n - Troubleshoot complex build failures, pipeline bottlenecks, and infrastructure issues, driving root-cause analysis and implementing durable fixes.\n\n - Design and drive improvements to internal build infrastructure, test infrastructure, developer tooling, and automation that increase developer velocity and engineering productivity.\n\n - Identify systemic bottlenecks across developer workflows and lead architectural improvements to developer infrastructure.\n\n - Contribute to the company’s efforts around AI tooling to improve engineering productivity and automate repetitive workflows.\n\n - Provide technical leadership across projects, influence engineering standards, and mentor other engineers within the Developer Productivity organization.\n\n - Participate in on-call and incident response for Developer Productivity systems and services.\n\n\n\nSkills & Qualifications\n\n - 7+ years of professional experience in software engineering, infrastructure engineering, DevOps, developer productivity, or a related area.\n\n - Deep hands-on experience with CI/CD systems and building or evolving automated build, test, and deployment infrastructure.\n\n - Experience with artifact repositories, software packaging, dependency management, and reproducible build concepts.\n\n - Experience with cloud computing platforms, with AWS preferred, and programmatic infrastructure provisioning.\n\n - Strong experience with distributed version control systems, code review workflows, branching strategies, and repository management.\n\n - Strong understanding of Linux/Unix systems, networking fundamentals, and scripting or programming for automation.\n\n - Experience with containerization and container orchestration, with Kubernetes preferred.\n\n - Strong troubleshooting skills and the ability to debug complex distributed systems and infrastructure issues.\n\n - Demonstrated experience leading technical initiatives across multiple teams and driving improvements to developer infrastructure at organizational scale.\n\n - Ability to identify architectural bottlenecks, evaluate tradeoffs, and drive long-term improvements rather than only addressing operational issues.\n\n - Experience operating production systems and participating in on-call, incident response, and postmortem processes.\n\n\n\nPreferred Skills & Qualifications\n\n - Experience with infrastructure-as-code tools and practices.\n\n - Proficiency in Python, Go, Shell, or another language used for infrastructure automation and developer tooling.\n\n - Experience with build systems, build graph optimization, or large-scale build infrastructure.\n\n - Experience with observability practices including monitoring, logging, alerting, and performance analysis.\n\n - Experience building internal developer platforms, self-service tooling, or developer-facing infrastructure.\n\n - Experience applying AI/LLM tooling to engineering workflows or developer productivity.\n\n - BS/MS in Computer Science or a related field, or equivalent practical experience.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"8318fcc4-cda9-426c-8ff5-9c8c01408268","title":"Staff Cloud Infrastructure Engineer","department":"Software Engineering ","team":"Developer Productivity","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[{"location":"Toronto, CAN","address":{"postalAddress":{"addressRegion":"Ontario ","addressCountry":"Canada","addressLocality":"Toronto "}}}],"publishedAt":"2026-09-01T18:56:26.667+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressRegion":"California ","addressCountry":"United States","addressLocality":"Sunnyvale "}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/8318fcc4-cda9-426c-8ff5-9c8c01408268","applyUrl":"https://jobs.ashbyhq.com/cerebras/8318fcc4-cda9-426c-8ff5-9c8c01408268/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Responsibilities:
Drive the design and architecture of secure, scalable cloud infrastructure and identity platforms in AWS and our own data centers.
Design and implement IAM, IGA, authentication, authorization, SSO, MFA, identity lifecycle management, and provisioning/deprovisioning solutions using modern identity platforms and standards such as SAML, OAuth2, OIDC, and SCIM.
Develop automation, integrations, and infrastructure-as-code solutions using Terraform and programming languages such as Python and Go.
Design and implement security controls for AI-powered systems, including controlled, audited, and governed agent workflows, while contributing to core security services such as service identity, secrets management, key management, authentication, and authorization.
Partner across Security, Engineering, and Infrastructure teams to drive secure-by-design solutions, implement Zero Trust principles, and reduce operational friction.
Drive technical direction and cross-team initiatives that improve the scalability, reliability, security, and developer experience of our infrastructure.
Write high-quality, reliable code, participate in architecture and code reviews, mentor engineers, and help raise the technical bar across the team.
Support critical production systems and drive operational excellence through scalability, resiliency, observability, and automation.
Participate in on-call and incident response for the Developer Productivity organization.
Skills & Qualifications
7+ years of experience in Cloud Infrastructure, Platform Engineering, Identity & Access Management, Identity Engineering, or Security Engineering.
Proven experience designing and owning complex production infrastructure or platform systems at scale.
Strong knowledge of authentication, authorization, identity lifecycle management, and federation protocols including SAML, OAuth2, OIDC, SCIM, and RBAC.
Experience designing and operating identity and access controls within AWS environments, with hands-on experience building and operating production-level services on AWS.
Experience working with container technologies and deploying and operating services on Kubernetes.
Strong automation and coding skills with Python or Go, along with Terraform or similar IaC technologies.
A security-first mindset with experience implementing Zero Trust, least-privilege access, and compliance frameworks such as SOC2, FedRAMP, or ITAR.
A strong platform and operational mindset, with experience supporting and improving production services through monitoring, troubleshooting, incident response, and automation.
Demonstrated ability to influence technical direction, drive cross-team initiatives, and mentor other engineers.
Excellent collaboration and communication skills, with a proven ability to work across teams and influence technical decisions.
Preferred Skills & Qualifications
Hands-on experience with identity platforms such as Okta, Microsoft Entra ID (Azure AD), or modern IAM/IGA platforms.
Experience with Azure and/or GCP is a bonus.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nResponsibilities:\n\n - Drive the design and architecture of secure, scalable cloud infrastructure and identity platforms in AWS and our own data centers.\n\n - Design and implement IAM, IGA, authentication, authorization, SSO, MFA, identity lifecycle management, and provisioning/deprovisioning solutions using modern identity platforms and standards such as SAML, OAuth2, OIDC, and SCIM.\n\n - Develop automation, integrations, and infrastructure-as-code solutions using Terraform and programming languages such as Python and Go.\n\n - Design and implement security controls for AI-powered systems, including controlled, audited, and governed agent workflows, while contributing to core security services such as service identity, secrets management, key management, authentication, and authorization.\n\n - Partner across Security, Engineering, and Infrastructure teams to drive secure-by-design solutions, implement Zero Trust principles, and reduce operational friction.\n\n - Drive technical direction and cross-team initiatives that improve the scalability, reliability, security, and developer experience of our infrastructure.\n\n - Write high-quality, reliable code, participate in architecture and code reviews, mentor engineers, and help raise the technical bar across the team.\n\n - Support critical production systems and drive operational excellence through scalability, resiliency, observability, and automation.\n\n - Participate in on-call and incident response for the Developer Productivity organization.\n\n\n\nSkills & Qualifications\n\n - 7+ years of experience in Cloud Infrastructure, Platform Engineering, Identity & Access Management, Identity Engineering, or Security Engineering.\n\n - Proven experience designing and owning complex production infrastructure or platform systems at scale.\n\n - Strong knowledge of authentication, authorization, identity lifecycle management, and federation protocols including SAML, OAuth2, OIDC, SCIM, and RBAC.\n\n - Experience designing and operating identity and access controls within AWS environments, with hands-on experience building and operating production-level services on AWS.\n\n - Experience working with container technologies and deploying and operating services on Kubernetes.\n\n - Strong automation and coding skills with Python or Go, along with Terraform or similar IaC technologies.\n\n - A security-first mindset with experience implementing Zero Trust, least-privilege access, and compliance frameworks such as SOC2, FedRAMP, or ITAR.\n\n - A strong platform and operational mindset, with experience supporting and improving production services through monitoring, troubleshooting, incident response, and automation.\n\n - Demonstrated ability to influence technical direction, drive cross-team initiatives, and mentor other engineers.\n\n - Excellent collaboration and communication skills, with a proven ability to work across teams and influence technical decisions.\n\n\n\nPreferred Skills & Qualifications\n\n - Hands-on experience with identity platforms such as Okta, Microsoft Entra ID (Azure AD), or modern IAM/IGA platforms.\n\n - Experience with Azure and/or GCP is a bonus.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"5ddcef34-82e8-4e20-9938-47aa49e6418d","title":"Staff AI Engineer – Business Systems ","department":"IT & Security","team":"IT","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2026-09-02T13:53:38.260+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressRegion":"California ","addressCountry":"United States","addressLocality":"Sunnyvale "}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/5ddcef34-82e8-4e20-9938-47aa49e6418d","applyUrl":"https://jobs.ashbyhq.com/cerebras/5ddcef34-82e8-4e20-9938-47aa49e6418d/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Hands-on AI engineering, solution architecture and compliance-by-design for enterprise Finance, operations and business systems
Responsibilities
The role is accountable for hands-on delivery and architecture within its layer, with shared governance across BIS, Finance, Business Operations, IT and Security and active partnership with other enterprise functions.
AI solution architecture
Design end-to-end agentic solutions and determine when a use case should query a source system directly versus use the unified data model.
Partner with stakeholders to identify high-value use cases, translate requirements into controlled AI workflows and select AI, conventional automation or no new technology.
Create reusable architecture patterns for agents, tools, APIs, MCP servers, prompts, evaluations and human-review workflows.
Produce solution designs, security flows, deployment patterns and technical standards.
AI engineering and system enablement
Build AI agents, orchestration services, enterprise applications and reusable platform components.
Deliver workflows for close and reporting, procurement, forecasting, billing and compliance monitoring where AI adds measurable value.
Establish secure, primarily read-only AI connections to approved business systems, beginning with NetSuite and extending to adjacent Finance and enterprise platforms as priorities evolve.
Preserve source-system authentication, authorization, user-level entitlements, rate limits and audit trails.
Implement citations, evidence links, deterministic checks, exception handling and safe action boundaries.
Prototype-to-enterprise delivery
Assess business-built or rapidly developed prototypes for value, architecture, security, maintainability and control readiness.
Refactor or rebuild approved prototypes into tested, monitored and supportable enterprise applications.
Establish development, test and production environments, release pipelines, incident response and rollback controls.
AI platform strategy
Evaluate AI models, agent frameworks, connectors and enterprise platforms on a regular cadence.
Run structured proofs of concept and assess security, accuracy, integration, scalability, experience, cost and vendor viability.
Maintain platform standards and recommend adoption, retention, replacement or retirement decisions.
Organizational enablement and adoption
Create clear documentation, reusable patterns and reference architectures; coach teams on effective agent design, prompts, evaluation practices and safe operating boundaries.
Establish feedback loops with users and process owners; use adoption, task success, efficiency, trust and support signals to guide iteration.
Finance, SOX and compliance
Translate Finance, Security, Privacy, SOX and SSDLC requirements into technical architecture and application controls.
Implement least privilege, segregation of duties, logging, retention, evaluation, change control and audit evidence.
Require deterministic validation and reconciliation for financially material outputs.
Support SOX walkthroughs, control testing, audits, risk assessments and remediation while escalating formal approval to control owners.
CANDIDATE PROFILE
Qualifications, success measures and boundaries
Required capabilities are calibrated for a Staff-level hands-on engineer with solution-architecture responsibilities.
Required qualifications
8+ years in software, platform, integration, solution engineering or enterprise applications, including meaningful hands-on production ownership in complex environments.
Strong Python and/or TypeScript skills; experience with APIs, MCP or comparable tool protocols, enterprise authentication and distributed-system design.
Practical experience building production AI systems using agents, tool use, retrieval, structured outputs, evaluations and monitoring.
Practical familiarity with leading LLM platforms and agent frameworks, such as OpenAI, Anthropic, Gemini, LangChain, Semantic Kernel or comparable technologies, including prompt and context engineering.
Strong solution-architecture judgment across security, reliability, performance, cost, observability and supportability.
Working knowledge of enterprise Finance processes such as general ledger, close, reporting, procure-to-pay, order-to-cash, forecasting and management reporting.
Working knowledge of compliance-by-design, including access, segregation of duties, change management, interfaces, automated controls, completeness and accuracy, and audit evidence.
Ability to communicate with engineers, Finance leaders, control owners, Security and executives.
Preferred qualifications
Experience with ERPs, data platforms, frontier AI platforms, agent frameworks or comparable enterprise technologies.
Experience building internal enterprise applications.
Hands-on experience implementing SOX controls or operating in a public-company or audit-regulated environment.
Success measures
Time from approved use case to controlled production and sustained adoption, with evidence of measurable business value.
Reduction in manual effort and business-process cycle time; improvement in decision quality or service levels.
Accuracy, groundedness, reconciliation success and production reliability of deployed agents.
User adoption, task success, stakeholder trust and support burden for production workflows.
Latency, operating cost and cost per successful task for deployed agents and applications.
Reuse of approved architecture patterns and components across use cases.
Number of viable prototypes transitioned into governed enterprise solutions.
Security, SOX and audit findings; evidence completeness; incident rate and remediation time.
Quality and timeliness of AI platform evaluations and roadmap recommendations.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nHands-on AI engineering, solution architecture and compliance-by-design for enterprise Finance, operations and business systems\n\nResponsibilities\n\nThe role is accountable for hands-on delivery and architecture within its layer, with shared governance across BIS, Finance, Business Operations, IT and Security and active partnership with other enterprise functions.\n\nAI solution architecture\n\n - Design end-to-end agentic solutions and determine when a use case should query a source system directly versus use the unified data model.\n\n - Partner with stakeholders to identify high-value use cases, translate requirements into controlled AI workflows and select AI, conventional automation or no new technology.\n\n - Create reusable architecture patterns for agents, tools, APIs, MCP servers, prompts, evaluations and human-review workflows.\n\n - Produce solution designs, security flows, deployment patterns and technical standards.\n\nAI engineering and system enablement\n\n - Build AI agents, orchestration services, enterprise applications and reusable platform components.\n\n - Deliver workflows for close and reporting, procurement, forecasting, billing and compliance monitoring where AI adds measurable value.\n\n - Establish secure, primarily read-only AI connections to approved business systems, beginning with NetSuite and extending to adjacent Finance and enterprise platforms as priorities evolve.\n\n - Preserve source-system authentication, authorization, user-level entitlements, rate limits and audit trails.\n\n - Implement citations, evidence links, deterministic checks, exception handling and safe action boundaries.\n\nPrototype-to-enterprise delivery\n\n - Assess business-built or rapidly developed prototypes for value, architecture, security, maintainability and control readiness.\n\n - Refactor or rebuild approved prototypes into tested, monitored and supportable enterprise applications.\n\n - Establish development, test and production environments, release pipelines, incident response and rollback controls.\n\nAI platform strategy\n\n - Evaluate AI models, agent frameworks, connectors and enterprise platforms on a regular cadence.\n\n - Run structured proofs of concept and assess security, accuracy, integration, scalability, experience, cost and vendor viability.\n\n - Maintain platform standards and recommend adoption, retention, replacement or retirement decisions.\n\nOrganizational enablement and adoption\n\n - Create clear documentation, reusable patterns and reference architectures; coach teams on effective agent design, prompts, evaluation practices and safe operating boundaries.\n\n - Establish feedback loops with users and process owners; use adoption, task success, efficiency, trust and support signals to guide iteration.\n\nFinance, SOX and compliance\n\n - Translate Finance, Security, Privacy, SOX and SSDLC requirements into technical architecture and application controls.\n\n - Implement least privilege, segregation of duties, logging, retention, evaluation, change control and audit evidence.\n\n - Require deterministic validation and reconciliation for financially material outputs.\n\n - Support SOX walkthroughs, control testing, audits, risk assessments and remediation while escalating formal approval to control owners.\n\n\n\n\n\nCANDIDATE PROFILE\n\nQualifications, success measures and boundaries\n\nRequired capabilities are calibrated for a Staff-level hands-on engineer with solution-architecture responsibilities.\n\nRequired qualifications\n\n - 8+ years in software, platform, integration, solution engineering or enterprise applications, including meaningful hands-on production ownership in complex environments.\n\n - Strong Python and/or TypeScript skills; experience with APIs, MCP or comparable tool protocols, enterprise authentication and distributed-system design.\n\n - Practical experience building production AI systems using agents, tool use, retrieval, structured outputs, evaluations and monitoring.\n\n - Practical familiarity with leading LLM platforms and agent frameworks, such as OpenAI, Anthropic, Gemini, LangChain, Semantic Kernel or comparable technologies, including prompt and context engineering.\n\n - Strong solution-architecture judgment across security, reliability, performance, cost, observability and supportability.\n\n - Working knowledge of enterprise Finance processes such as general ledger, close, reporting, procure-to-pay, order-to-cash, forecasting and management reporting.\n\n - Working knowledge of compliance-by-design, including access, segregation of duties, change management, interfaces, automated controls, completeness and accuracy, and audit evidence.\n\n - Ability to communicate with engineers, Finance leaders, control owners, Security and executives.\n\nPreferred qualifications\n\n - Experience with ERPs, data platforms, frontier AI platforms, agent frameworks or comparable enterprise technologies.\n\n - Experience building internal enterprise applications.\n\n - Hands-on experience implementing SOX controls or operating in a public-company or audit-regulated environment.\n\nSuccess measures\n\n - Time from approved use case to controlled production and sustained adoption, with evidence of measurable business value.\n\n - Reduction in manual effort and business-process cycle time; improvement in decision quality or service levels.\n\n - Accuracy, groundedness, reconciliation success and production reliability of deployed agents.\n\n - User adoption, task success, stakeholder trust and support burden for production workflows.\n\n - Latency, operating cost and cost per successful task for deployed agents and applications.\n\n - Reuse of approved architecture patterns and components across use cases.\n\n - Number of viable prototypes transitioned into governed enterprise solutions.\n\n - Security, SOX and audit findings; evidence completeness; incident rate and remediation time.\n\n - Quality and timeliness of AI platform evaluations and roadmap recommendations.\n \n \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"099d8b10-9bf1-4287-88ab-f9a3274f45e1","title":"Physical Security Lead, Manufacturing Operations","department":"IT & Security","team":"Security","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2026-09-02T21:19:01.885+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressRegion":"California ","addressCountry":"United States","addressLocality":"Sunnyvale "}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/099d8b10-9bf1-4287-88ab-f9a3274f45e1","applyUrl":"https://jobs.ashbyhq.com/cerebras/099d8b10-9bf1-4287-88ab-f9a3274f45e1/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Cerebras is seeking an experienced Physical Security Lead, Manufacturing Operations to establish and govern physical security across all current and future contract manufacturing locations. Although Remote, the incumbent must be based in the San Francisco Bay, CA area. This is a hands-on individual-contributor role that reports to the Director, Global Physical Security and provides functional leadership without direct reports.
This role will help set and maintain minimum standards, assess risk, drive corrective actions, and oversee controls for sensitive-area entry, intellectual property protection, cleanroom-compatible operations, contract security services, security technology, and cargo and logistics security practices. The role is required to provide regular site visits and incident-based response.
Responsibilities
Serve as the primary Global Physical Security partner for current and future contract manufacturing locations; develop and govern minimum standards, site requirements, exceptions, and risk acceptance.
Conduct initial, recurring, and event-driven site assessments; prioritize findings, establish corrective actions, and verify closure.
Design and govern sensitive-area entry controls, including clean-in/clean-out (CICO), personal property and data bearing device (DBD) restrictions, visitor and contractor access, escorting, and exceptions, while aligning with cleanroom, ESD, life-safety, and production requirements.
Protect intellectual property, proprietary processes, prototypes, components, test equipment, finished products, and controlled materials through security zoning, access governance, visitor controls, and photography restrictions.
Act as the client security representative for partner-managed guard services; where Cerebras contracts directly, manage scope, post orders, training, service levels, performance metrics, and corrective actions.
Collaborate on Cerebras-managed access control, video surveillance, intrusion detection, visitor management, and alarm-monitoring systems, including design reviews, commissioning, and operational validation.
In partnership with internal stakeholders, define physical security requirements for new manufacturing partners, production lines, facility expansions, contracts, and statements of work.
Govern cargo and logistics security requirements, including chain of custody, secure staging, shipping and receiving, high-risk shipments, carrier handoffs, and third-party performance.
Respond to manufacturing-related security incidents, preserve relevant evidence, coordinate fact-finding, identify root causes, and track corrective actions.
Maintain regular site presence, security metrics, risk reporting, procedures, training, and concise updates for security and business leadership.
Skills and Qualifications
Minimum
Five or more years of progressively responsible physical security experience directly supporting manufacturing, industrial, semiconductor, electronics, computing hardware, or a comparable operational environment.
Demonstrated experience implementing security controls in active manufacturing operations while balancing production, safety, quality, cleanroom or ESD requirements, and continuity.
Experience supporting contract manufacturers, suppliers, or partner-operated facilities through standards, assessments, governance, and stakeholder influence.
Experience protecting intellectual property, proprietary processes, prototypes, high-value components, products, or sensitive technical information, including CICO or comparable sensitive-area entry controls.
Working knowledge of access control, video surveillance, intrusion detection, visitor management, alarm monitoring, and contract security service oversight.
Familiarity with cargo security, chain-of-custody controls, secure shipping and receiving, logistics-provider governance, and manufacturing incident response.
Strong risk-assessment, project-management, written-communication, analytical, and stakeholder-influence skills.
Preferred
Physical security experience in semiconductor, advanced electronics, computing hardware, or another intellectual-property-intensive manufacturing sector, including cleanrooms, new-product introduction, or production ramps.
Experience with Genetec or a comparable enterprise physical security platform.
Familiarity with relevant security and supply-chain frameworks, such as CTPAT, TAPA, ISO 28000, ISO/IEC 27001 and 27002, NIST SP 800-53 and SP 800-171, as applicable.
Bachelor's degree in relevant discipline or an equivalent combination of education and directly related experience.
ASIS CPP, PSP, or PCI certification.
Location and Travel
It requires regular site presence at current and future contract manufacturing locations in and around Sunnyvale, CA, approximately 30-40% travel, and occasional evening, weekend, or short-notice support for significant incidents or operational requirements.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nCerebras is seeking an experienced Physical Security Lead, Manufacturing Operations to establish and govern physical security across all current and future contract manufacturing locations. Although Remote, the incumbent must be based in the San Francisco Bay, CA area. This is a hands-on individual-contributor role that reports to the Director, Global Physical Security and provides functional leadership without direct reports.\n\nThis role will help set and maintain minimum standards, assess risk, drive corrective actions, and oversee controls for sensitive-area entry, intellectual property protection, cleanroom-compatible operations, contract security services, security technology, and cargo and logistics security practices. The role is required to provide regular site visits and incident-based response.\n\nResponsibilities\n\n - Serve as the primary Global Physical Security partner for current and future contract manufacturing locations; develop and govern minimum standards, site requirements, exceptions, and risk acceptance.\n\n - Conduct initial, recurring, and event-driven site assessments; prioritize findings, establish corrective actions, and verify closure.\n\n - Design and govern sensitive-area entry controls, including clean-in/clean-out (CICO), personal property and data bearing device (DBD) restrictions, visitor and contractor access, escorting, and exceptions, while aligning with cleanroom, ESD, life-safety, and production requirements.\n\n - Protect intellectual property, proprietary processes, prototypes, components, test equipment, finished products, and controlled materials through security zoning, access governance, visitor controls, and photography restrictions.\n\n - Act as the client security representative for partner-managed guard services; where Cerebras contracts directly, manage scope, post orders, training, service levels, performance metrics, and corrective actions.\n\n - Collaborate on Cerebras-managed access control, video surveillance, intrusion detection, visitor management, and alarm-monitoring systems, including design reviews, commissioning, and operational validation.\n\n - In partnership with internal stakeholders, define physical security requirements for new manufacturing partners, production lines, facility expansions, contracts, and statements of work.\n\n - Govern cargo and logistics security requirements, including chain of custody, secure staging, shipping and receiving, high-risk shipments, carrier handoffs, and third-party performance.\n\n - Respond to manufacturing-related security incidents, preserve relevant evidence, coordinate fact-finding, identify root causes, and track corrective actions.\n\n - Maintain regular site presence, security metrics, risk reporting, procedures, training, and concise updates for security and business leadership.\n\nSkills and Qualifications\n\nMinimum\n\n - Five or more years of progressively responsible physical security experience directly supporting manufacturing, industrial, semiconductor, electronics, computing hardware, or a comparable operational environment.\n\n - Demonstrated experience implementing security controls in active manufacturing operations while balancing production, safety, quality, cleanroom or ESD requirements, and continuity.\n\n - Experience supporting contract manufacturers, suppliers, or partner-operated facilities through standards, assessments, governance, and stakeholder influence.\n\n - Experience protecting intellectual property, proprietary processes, prototypes, high-value components, products, or sensitive technical information, including CICO or comparable sensitive-area entry controls.\n\n - Working knowledge of access control, video surveillance, intrusion detection, visitor management, alarm monitoring, and contract security service oversight.\n\n - Familiarity with cargo security, chain-of-custody controls, secure shipping and receiving, logistics-provider governance, and manufacturing incident response.\n\n - Strong risk-assessment, project-management, written-communication, analytical, and stakeholder-influence skills.\n\nPreferred\n\n - Physical security experience in semiconductor, advanced electronics, computing hardware, or another intellectual-property-intensive manufacturing sector, including cleanrooms, new-product introduction, or production ramps.\n\n - Experience with Genetec or a comparable enterprise physical security platform.\n\n - Familiarity with relevant security and supply-chain frameworks, such as CTPAT, TAPA, ISO 28000, ISO/IEC 27001 and 27002, NIST SP 800-53 and SP 800-171, as applicable.\n\n - Bachelor's degree in relevant discipline or an equivalent combination of education and directly related experience.\n\n - ASIS CPP, PSP, or PCI certification.\n\nLocation and Travel\n\nIt requires regular site presence at current and future contract manufacturing locations in and around Sunnyvale, CA, approximately 30-40% travel, and occasional evening, weekend, or short-notice support for significant incidents or operational requirements.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"d114d16b-3c5f-44a1-9a15-26b37fb45369","title":"Detection and Response Platform Engineer","department":"IT & Security","team":"Security","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2026-09-02T21:24:23.626+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressRegion":"California ","addressCountry":"United States","addressLocality":"Sunnyvale "}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/d114d16b-3c5f-44a1-9a15-26b37fb45369","applyUrl":"https://jobs.ashbyhq.com/cerebras/d114d16b-3c5f-44a1-9a15-26b37fb45369/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
We are seeking a senior Detection and Response Platform Engineer to own and evolve the systems and tooling that power our detection and response program. You will build and operate the services that move and shape security telemetry, execute detection logic reliably, and enable automation that makes investigation faster and more consistent. This is an engineering role on the Detection and Response team, focused on building durable internal systems that other engineers rely on, with strong expectations around reliability, operability, and developer experience.
Own and evolve the core infrastructure that powers detection and response workflows at scale.
Design and maintain security telemetry pipelines, including collection, normalization, enrichment, and retention of logs and events.
Own and evolve the execution environment and supporting tooling for detections and response automation, including dependency and configuration management, release processes, and runtime health monitoring.
Automate investigation and response workflows by extending integrations across the tools we rely on.
Set and uphold engineering standards for our tooling: clear interfaces, automated tests, code review, and documentation that makes the system easy to extend.
Own operational health for the platform, including metrics, alerting, and on-call responsibilities focused on system reliability and availability.
Explore and apply emerging approaches, potentially leveraging AI, to reduce toil and strengthen our security posture.
Maintain operational playbooks and procedures that keep the platform healthy and make failures fast to diagnose and recover from.
5+ years of experience in cloud infrastructure, platform/SRE, software engineering, or security engineering with a strong infrastructure focus.
Strong proficiency in Python, with the ability to write clean, maintainable, and testable code for production systems.
Hands-on experience operating production systems in a major cloud environment (AWS, Azure, or GCP), including IAM, networking, and logging/auditing.
Experience building and operating event/log pipelines and data workflows (streaming and/or batch), with strong fundamentals in reliability and data quality.
Experience with infrastructure as code and deployment automation (e.g., Terraform/Pulumi and CI/CD).
Practical knowledge of detection and response concepts across cloud, identity, and endpoint environments, with the ability to partner effectively with D&R engineers.
Strong fundamentals in operating systems, networking, and troubleshooting distributed systems.
Excellent written communication skills, with the ability to create clear documentation and runbooks.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nWe are seeking a senior Detection and Response Platform Engineer to own and evolve the systems and tooling that power our detection and response program. You will build and operate the services that move and shape security telemetry, execute detection logic reliably, and enable automation that makes investigation faster and more consistent. This is an engineering role on the Detection and Response team, focused on building durable internal systems that other engineers rely on, with strong expectations around reliability, operability, and developer experience.\n\n\nRESPONSIBILITIES\n\n - Own and evolve the core infrastructure that powers detection and response workflows at scale.\n\n - Design and maintain security telemetry pipelines, including collection, normalization, enrichment, and retention of logs and events.\n\n - Own and evolve the execution environment and supporting tooling for detections and response automation, including dependency and configuration management, release processes, and runtime health monitoring.\n\n - Automate investigation and response workflows by extending integrations across the tools we rely on.\n\n - Set and uphold engineering standards for our tooling: clear interfaces, automated tests, code review, and documentation that makes the system easy to extend.\n\n - Own operational health for the platform, including metrics, alerting, and on-call responsibilities focused on system reliability and availability.\n\n - Explore and apply emerging approaches, potentially leveraging AI, to reduce toil and strengthen our security posture.\n\n - Maintain operational playbooks and procedures that keep the platform healthy and make failures fast to diagnose and recover from.\n\n\nSKILLS AND QUALIFICATIONS\n\n - 5+ years of experience in cloud infrastructure, platform/SRE, software engineering, or security engineering with a strong infrastructure focus.\n\n - Strong proficiency in Python, with the ability to write clean, maintainable, and testable code for production systems.\n\n - Hands-on experience operating production systems in a major cloud environment (AWS, Azure, or GCP), including IAM, networking, and logging/auditing.\n\n - Experience building and operating event/log pipelines and data workflows (streaming and/or batch), with strong fundamentals in reliability and data quality.\n\n - Experience with infrastructure as code and deployment automation (e.g., Terraform/Pulumi and CI/CD).\n\n - Practical knowledge of detection and response concepts across cloud, identity, and endpoint environments, with the ability to partner effectively with D&R engineers.\n\n - Strong fundamentals in operating systems, networking, and troubleshooting distributed systems.\n\n - Excellent written communication skills, with the ability to create clear documentation and runbooks.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"e616412a-6412-4f0d-93b9-47644d3e99fa","title":"PCB Layout Engineering Lead","department":"Hardware","team":"Systems","employmentType":"FullTime","location":"Remote (US)","secondaryLocations":[{"location":"Sunnyvale, CA","address":{"postalAddress":{"addressRegion":"California ","addressCountry":"United States","addressLocality":"Sunnyvale "}}}],"publishedAt":"2026-09-03T16:41:47.071+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressCountry":"United States"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/e616412a-6412-4f0d-93b9-47644d3e99fa","applyUrl":"https://jobs.ashbyhq.com/cerebras/e616412a-6412-4f0d-93b9-47644d3e99fa/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Cerebras is seeking an exceptional PCB Layout Lead to own the physical implementation of complex, high-performance printed circuit boards for AI systems. This role will translate schematics and engineering requirements into production-ready layouts, optimizing signal integrity, power integrity, thermal performance, reliability, and manufacturability.
Responsibilities
Own multilayer PCB layout from initial component placement through fabrication and assembly release.
Translate schematics, mechanical constraints, and electrical requirements into constraint-driven board designs using industry-standard PCB layout tools.
Define and implement board stackups, controlled-impedance structures, routing rules, reference planes, return paths, and length- and phase-matching constraints.
Place and route high-speed digital, high-current power, and sensitive analog circuits, including dense BGA fanout and differential interfaces.
Apply signal-integrity and power-integrity best practices to minimize crosstalk, discontinuities, noise, voltage drop, and electromagnetic interference.
Collaborate with electrical, SI/PI, mechanical, thermal, compliance, manufacturing, and test engineers to establish constraints and resolve layout issues.
Work with fabrication and assembly partners to select materials, validate stackups and via structures, and improve yield, cost, and schedule.
Perform design reviews and DFM, DFA, and DFT checks; generate and verify fabrication drawings, assembly drawings, drill data, Gerbers, ODB++, IPC-2581, and related release packages.
Maintain component footprints, padstacks, design libraries, layout standards, and release documentation.
Support prototype builds, board bring-up, failure analysis, and layout revisions through production.
Minimum Qualifications
Bachelor’s degree in electrical engineering, electronics engineering, or a related field, or equivalent practical experience.
10+ years of hands-on experience laying out complex, high-speed, multilayer printed circuit boards.
Expertise with Cadence Allegro PCB Designer and Constraint Manager; experience with Altium Designer or equivalent tools is also relevant.
Strong knowledge of component placement, controlled-impedance routing, differential pairs, length matching, return-path continuity, and power distribution.
Experience with dense BGA escape routing, HDI structures, blind and buried vias, microvias, via-in-pad, and backdrilling.
Working knowledge of signal integrity, power integrity, EMI/EMC, thermal design, creepage and clearance, and high-current routing.
Experience applying IPC standards and fabrication, assembly, test, and manufacturability requirements.
Ability to create and review complete PCB fabrication and assembly release packages.
Ability to thrive in a fast-paced, dynamic environment and adapt to changing priorities.
Excellent collaborative and interpersonal skills with multi-disciplined teams.
Experience working on server hardware, AI accelerators, hardware accelerator, datacenter, AI Hardware, enterprise product, GPU, CPU, TPU, server platform etc.
Preferred Qualifications
Experience designing large, high-layer-count boards for compute, networking, server, or AI accelerator systems.
Experience routing high-speed interfaces such as DDR4/DDR5, PCIe Gen4/Gen5 or later, Ethernet, USB, and multi-gigabit SerDes.
Experience with high-current, low-voltage power delivery, VRM placement, decoupling strategy, copper balancing, and thermal optimization.
Experience developing Allegro SKILL, scripts, or automation that improves layout quality and release efficiency.
Demonstrated success delivering first-pass functional boards and supporting products from prototype through volume production.
Location: Remote. Sunnyvale, CA (Hybrid) is highly preferred.
The base salary range for this position is $210,000 – $230,000+ annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nCerebras is seeking an exceptional PCB Layout Lead to own the physical implementation of complex, high-performance printed circuit boards for AI systems. This role will translate schematics and engineering requirements into production-ready layouts, optimizing signal integrity, power integrity, thermal performance, reliability, and manufacturability.\n\n\n\nResponsibilities\n\n - Own multilayer PCB layout from initial component placement through fabrication and assembly release.\n\n - Translate schematics, mechanical constraints, and electrical requirements into constraint-driven board designs using industry-standard PCB layout tools.\n\n - Define and implement board stackups, controlled-impedance structures, routing rules, reference planes, return paths, and length- and phase-matching constraints.\n\n - Place and route high-speed digital, high-current power, and sensitive analog circuits, including dense BGA fanout and differential interfaces.\n\n - Apply signal-integrity and power-integrity best practices to minimize crosstalk, discontinuities, noise, voltage drop, and electromagnetic interference.\n\n - Collaborate with electrical, SI/PI, mechanical, thermal, compliance, manufacturing, and test engineers to establish constraints and resolve layout issues.\n\n - Work with fabrication and assembly partners to select materials, validate stackups and via structures, and improve yield, cost, and schedule.\n\n - Perform design reviews and DFM, DFA, and DFT checks; generate and verify fabrication drawings, assembly drawings, drill data, Gerbers, ODB++, IPC-2581, and related release packages.\n\n - Maintain component footprints, padstacks, design libraries, layout standards, and release documentation.\n\n - Support prototype builds, board bring-up, failure analysis, and layout revisions through production.\n\nMinimum Qualifications\n\n - Bachelor’s degree in electrical engineering, electronics engineering, or a related field, or equivalent practical experience.\n\n - 10+ years of hands-on experience laying out complex, high-speed, multilayer printed circuit boards.\n\n - Expertise with Cadence Allegro PCB Designer and Constraint Manager; experience with Altium Designer or equivalent tools is also relevant.\n\n - Strong knowledge of component placement, controlled-impedance routing, differential pairs, length matching, return-path continuity, and power distribution.\n\n - Experience with dense BGA escape routing, HDI structures, blind and buried vias, microvias, via-in-pad, and backdrilling.\n\n - Working knowledge of signal integrity, power integrity, EMI/EMC, thermal design, creepage and clearance, and high-current routing.\n\n - Experience applying IPC standards and fabrication, assembly, test, and manufacturability requirements.\n\n - Ability to create and review complete PCB fabrication and assembly release packages.\n\n - Ability to thrive in a fast-paced, dynamic environment and adapt to changing priorities.\n\n - Excellent collaborative and interpersonal skills with multi-disciplined teams.\n\n - Experience working on server hardware, AI accelerators, hardware accelerator, datacenter, AI Hardware, enterprise product, GPU, CPU, TPU, server platform etc.\n\nPreferred Qualifications\n\n - Experience designing large, high-layer-count boards for compute, networking, server, or AI accelerator systems.\n\n - Experience routing high-speed interfaces such as DDR4/DDR5, PCIe Gen4/Gen5 or later, Ethernet, USB, and multi-gigabit SerDes.\n\n - Experience with high-current, low-voltage power delivery, VRM placement, decoupling strategy, copper balancing, and thermal optimization.\n\n - Experience developing Allegro SKILL, scripts, or automation that improves layout quality and release efficiency.\n\n - Demonstrated success delivering first-pass functional boards and supporting products from prototype through volume production.\n\nLocation: Remote. Sunnyvale, CA (Hybrid) is highly preferred.\n\n - The base salary range for this position is $210,000 – $230,000+ annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"3e85f230-6fe2-440f-8f31-c8419a295068","title":"Power Engineering Architect ","department":"Hardware","team":"Systems","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2026-09-03T17:03:38.717+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressRegion":"California ","addressCountry":"United States","addressLocality":"Sunnyvale "}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/3e85f230-6fe2-440f-8f31-c8419a295068","applyUrl":"https://jobs.ashbyhq.com/cerebras/3e85f230-6fe2-440f-8f31-c8419a295068/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Cerebras is seeking an exceptional Power Architect to lead our product power roadmap and technology development. This role is focusing on defining and driving power delivery architecture and strategy for high-performance compute, AI/ML accelerators and advanced ASIC platforms.
Responsibilities
Lead system architecture exploration with a focus on power delivery and thermal management.
Drive innovation in vertical power delivery to the wafer, enabling ultra-high current density solutions.
Collaborate with internal product, ASIC, and systems teams to define and refine detailed power specifications.
Architect power delivery systems optimized for both electrical performance and cooling efficiency.
Evaluate and select optimal architectures and strategic partners/vendors for new technology development.
Oversee the full lifecycle of power delivery solutions—from concept through production deployment.
Collaborate with package, silicon, PCB, and mechanical to optimize power delivery
Minimum Qualifications
MSEE or MSCE required; PhD preferred or equivalent industry experience.
15+ years of hands-on experience in power delivery systems.
Strong foundation in energy-efficient system design and associated trade-offs.
Practical experience in thermal modeling and cooling solution implementation.
High-current, low-voltage power delivery for advanced silicon
Experience with multiphase buck regulators, digital power controllers, DrMOS, smart power stages, and integrated voltage regulators
Excellent interpersonal skills and a collaborative mindset.
Experience working on server hardware, AI accelerators, hardware accelerator, datacenter, AI Hardware, enterprise product, GPU, CPU, TPU, server platform etc.
Preferred Qualifications
Demonstrated expertise in DC-DC power conversion, including control loops, power management, magnetics, and filter design.
Solid background in semiconductor technologies, including PMICs and integrated power modules.
Deep technical knowledge of magnetic components, particularly in custom inductor design.
Experience in developing advanced power modules with optimized thermal and magnetic characteristics.
Experience on package PDN design, power vias, bumps, interposers, substrates, and ASIC power delivery structure
Deep expertise on power architecture for chiplet-based designs, IVRs, advanced packages, or 2.5D/3D integration
Location: Sunnyvale, CA
The base salary range for this position is $230,000 to $275,000+ annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nCerebras is seeking an exceptional Power Architect to lead our product power roadmap and technology development. This role is focusing on defining and driving power delivery architecture and strategy for high-performance compute, AI/ML accelerators and advanced ASIC platforms.\n\n\n\nResponsibilities\n\n - Lead system architecture exploration with a focus on power delivery and thermal management.\n\n - Drive innovation in vertical power delivery to the wafer, enabling ultra-high current density solutions.\n\n - Collaborate with internal product, ASIC, and systems teams to define and refine detailed power specifications.\n\n - Architect power delivery systems optimized for both electrical performance and cooling efficiency.\n\n - Evaluate and select optimal architectures and strategic partners/vendors for new technology development.\n\n - Oversee the full lifecycle of power delivery solutions—from concept through production deployment.\n\n - Collaborate with package, silicon, PCB, and mechanical to optimize power delivery\n\nMinimum Qualifications\n\n - MSEE or MSCE required; PhD preferred or equivalent industry experience.\n\n - 15+ years of hands-on experience in power delivery systems.\n\n - Strong foundation in energy-efficient system design and associated trade-offs.\n\n - Practical experience in thermal modeling and cooling solution implementation.\n\n - High-current, low-voltage power delivery for advanced silicon\n\n - Experience with multiphase buck regulators, digital power controllers, DrMOS, smart power stages, and integrated voltage regulators\n\n - Excellent interpersonal skills and a collaborative mindset.\n\n - Experience working on server hardware, AI accelerators, hardware accelerator, datacenter, AI Hardware, enterprise product, GPU, CPU, TPU, server platform etc.\n\nPreferred Qualifications\n\n - Demonstrated expertise in DC-DC power conversion, including control loops, power management, magnetics, and filter design.\n\n - Solid background in semiconductor technologies, including PMICs and integrated power modules.\n\n - Deep technical knowledge of magnetic components, particularly in custom inductor design.\n\n - Experience in developing advanced power modules with optimized thermal and magnetic characteristics.\n\n - Experience on package PDN design, power vias, bumps, interposers, substrates, and ASIC power delivery structure\n\n - Deep expertise on power architecture for chiplet-based designs, IVRs, advanced packages, or 2.5D/3D integration\n\nLocation: Sunnyvale, CA\n\nThe base salary range for this position is $230,000 to $275,000+ annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"4197a749-fd21-4420-8d01-1df94c96310b","title":"Lead Systems Signal Integrity/Power Integrity Engineer","department":"Hardware","team":"Systems","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[],"publishedAt":"2026-09-03T17:58:01.475+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California ","addressCountry":"United States","addressLocality":"Sunnyvale "}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/4197a749-fd21-4420-8d01-1df94c96310b","applyUrl":"https://jobs.ashbyhq.com/cerebras/4197a749-fd21-4420-8d01-1df94c96310b/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
We are seeking an experienced System Signal Integrity and Power Integrity Engineer Lead to solve complex, high‑impact integrity challenges in next‑generation AI compute systems. This role is focused on deep technical analysis and hands‑on problem solving across high‑speed interfaces, power delivery networks, rigid and flex interconnects, and advanced packaging.
The ideal candidate is a technical expert engaged to resolve difficult SI/PI problems spanning silicon, package, PCB, flex, and connector domains.
Key Responsibilities:
- Solve complex signal integrity and power integrity problems for high‑speed AI compute platforms, including chip‑to‑chip and chip‑to‑board interfaces.
- Perform advanced pre‑layout and post‑layout SI/PI analysis across PCBs, flex circuits, rigid‑flex assemblies, connectors, and advanced packages.
- Lead root‑cause analysis of challenging SI/PI issues such as margin shortfalls, impedance discontinuities, coupling, resonances, and simulation‑to‑hardware mismatches.
- Analyze and resolve SI/PI challenges associated with flex circuits, high‑speed flex connectors, interposers, and advanced packaging technologies.
- Analyze and troubleshoot power delivery networks using DC and AC simulations and hardware correlation to resolve performance and stability issues.
- Define and refine PCB, rigid‑flex, and flex circuit stack‑ups, material selections, and impedance structures as required to meet performance targets.
- Review schematics, PCB layouts, and flex designs to identify SI/PI risks and recommend targeted design changes.
- Work closely with silicon and package design teams to resolve SI/PI issues related to bump/ball assignments, package‑to‑PCB transitions, and interface interactions.
- Act as a technical escalation point for complex SI/PI issues across multiple programs.
Minimum Qualifications:
- Master’s degree in Electrical Engineering.
- 15+ years of demonstrated depth of expertise in system-level signal integrity and power integrity engineering for high‑speed hardware systems.
Required Experience and Skills:
- Deep expertise in high‑speed serial and parallel interface analysis and debug.
- Strong hands‑on experience with PCB, rigid‑flex, and flex circuit stack‑up design and analysis.
- Advanced SI/PI analysis of flex connectors, high‑density interconnects, and advanced packaging technologies.
- Proficiency with 2D and 3D electromagnetic simulation tools.
- Power delivery network analysis, simulation, and lab correlation at the system level.
- Strong grounding in transmission line theory, microwave engineering, and high‑speed design fundamentals.
- Proven ability to correlate simulation results with hardware behavior and drive concrete design fixes.
-Experience working on server hardware, AI accelerators, hardware accelerator, datacenter, AI Hardware, enterprise product, GPU, CPU, TPU, server platform etc.
Additional Information:
- Experience with large‑scale AI or high-performance compute systems is preferred.
Location: Sunnyvale, CA
The base salary range for this position is $220,000 to $250,000+ annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nWe are seeking an experienced System Signal Integrity and Power Integrity Engineer Lead to solve complex, high‑impact integrity challenges in next‑generation AI compute systems. This role is focused on deep technical analysis and hands‑on problem solving across high‑speed interfaces, power delivery networks, rigid and flex interconnects, and advanced packaging. \n \nThe ideal candidate is a technical expert engaged to resolve difficult SI/PI problems spanning silicon, package, PCB, flex, and connector domains. \n \nKey Responsibilities: \n- Solve complex signal integrity and power integrity problems for high‑speed AI compute platforms, including chip‑to‑chip and chip‑to‑board interfaces. \n- Perform advanced pre‑layout and post‑layout SI/PI analysis across PCBs, flex circuits, rigid‑flex assemblies, connectors, and advanced packages. \n- Lead root‑cause analysis of challenging SI/PI issues such as margin shortfalls, impedance discontinuities, coupling, resonances, and simulation‑to‑hardware mismatches. \n- Analyze and resolve SI/PI challenges associated with flex circuits, high‑speed flex connectors, interposers, and advanced packaging technologies. \n- Analyze and troubleshoot power delivery networks using DC and AC simulations and hardware correlation to resolve performance and stability issues. \n- Define and refine PCB, rigid‑flex, and flex circuit stack‑ups, material selections, and impedance structures as required to meet performance targets. \n- Review schematics, PCB layouts, and flex designs to identify SI/PI risks and recommend targeted design changes. \n- Work closely with silicon and package design teams to resolve SI/PI issues related to bump/ball assignments, package‑to‑PCB transitions, and interface interactions. \n- Act as a technical escalation point for complex SI/PI issues across multiple programs. \n \nMinimum Qualifications: \n- Master’s degree in Electrical Engineering. \n- 15+ years of demonstrated depth of expertise in system-level signal integrity and power integrity engineering for high‑speed hardware systems. \n \nRequired Experience and Skills: \n- Deep expertise in high‑speed serial and parallel interface analysis and debug. \n- Strong hands‑on experience with PCB, rigid‑flex, and flex circuit stack‑up design and analysis. \n- Advanced SI/PI analysis of flex connectors, high‑density interconnects, and advanced packaging technologies. \n- Proficiency with 2D and 3D electromagnetic simulation tools. \n- Power delivery network analysis, simulation, and lab correlation at the system level. \n- Strong grounding in transmission line theory, microwave engineering, and high‑speed design fundamentals. \n- Proven ability to correlate simulation results with hardware behavior and drive concrete design fixes.\n\n-Experience working on server hardware, AI accelerators, hardware accelerator, datacenter, AI Hardware, enterprise product, GPU, CPU, TPU, server platform etc.\n\n \nAdditional Information: \n- Experience with large‑scale AI or high-performance compute systems is preferred.\n\n\n\nLocation: Sunnyvale, CA\n\nThe base salary range for this position is $220,000 to $250,000+ annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"c35a389c-807e-45fb-bfda-03f6b1361871","title":"ML Systems Integration Engineer","department":"Software Engineering ","team":"CoDesign","employmentType":"FullTime","location":"Sunnyvale, CA","secondaryLocations":[{"location":"Toronto, CAN","address":{"postalAddress":{"postalCode":"M5H1Z5","addressRegion":"Ontario","streetAddress":"67 Richmond St W","addressCountry":"Canada","addressLocality":"Toronto"}}}],"publishedAt":"2026-09-03T18:54:24.775+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressRegion":"California ","addressCountry":"United States","addressLocality":"Sunnyvale "}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/c35a389c-807e-45fb-bfda-03f6b1361871","applyUrl":"https://jobs.ashbyhq.com/cerebras/c35a389c-807e-45fb-bfda-03f6b1361871/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Responsibilities
Participate in bring-up of next-generation AI hardware systems and supporting software infrastructure.
Debug complex system-level issues spanning hardware and software interactions.
Investigate failures occurring during system bring-up and identify root causes using logs, telemetry, and diagnostic tools.
Build automation frameworks and internal tooling that improve system validation and debugging workflows.
Develop software used to test, validate, and stress distributed hardware systems during development and production cycles.
Collaborate closely with hardware engineers to isolate and resolve system integration issues.
Improve system observability by building tools that surface failures quickly and accelerate debugging.
Reproduce, triage, and diagnose difficult issues that arise during early hardware deployment.
Support validation and qualification of new hardware generations as systems move toward production readiness.
Continuously improve internal engineering workflows related to debugging, testing, and automation.
Skills & Qualifications
BS or MS in Computer Science, Computer Engineering, Electrical Engineering, or related technical field.
Strong programming skills in Python and/or C++.
Excellent debugging and problem-solving skills with ability to investigate complex technical issues methodically.
Solid understanding of operating systems fundamentals (processes, threads, memory management, concurrency, IPC).
Experience working in Linux development environments.
Understanding of computer architecture and interactions between hardware and software systems.
Strong analytical thinking and ability to break down complex system failures into actionable root causes.
Ability to work effectively across multiple engineering teams and collaborate in highly technical environments.
Strong communication skills and willingness to work on ambiguous technical problems.
Preferred Skills & Qualifications
Experience building automation frameworks, internal tooling, or test infrastructure
Familiarity with distributed systems concepts
Experience debugging large-scale systems or complex infrastructure environments
Understanding of networking fundamentals and communication between distributed systems
Experience working with hardware-adjacent software or system integration environments
Familiarity with performance analysis, system telemetry, and log analysis
Exposure to production systems validation or infrastructure reliability engineering
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nResponsibilities\n\n - Participate in bring-up of next-generation AI hardware systems and supporting software infrastructure.\n\n - Debug complex system-level issues spanning hardware and software interactions.\n\n - Investigate failures occurring during system bring-up and identify root causes using logs, telemetry, and diagnostic tools.\n\n - Build automation frameworks and internal tooling that improve system validation and debugging workflows.\n\n - Develop software used to test, validate, and stress distributed hardware systems during development and production cycles.\n\n - Collaborate closely with hardware engineers to isolate and resolve system integration issues.\n\n - Improve system observability by building tools that surface failures quickly and accelerate debugging.\n\n - Reproduce, triage, and diagnose difficult issues that arise during early hardware deployment.\n\n - Support validation and qualification of new hardware generations as systems move toward production readiness.\n\n - Continuously improve internal engineering workflows related to debugging, testing, and automation.\n\n\n\nSkills & Qualifications\n\n - BS or MS in Computer Science, Computer Engineering, Electrical Engineering, or related technical field.\n\n - Strong programming skills in Python and/or C++.\n\n - Excellent debugging and problem-solving skills with ability to investigate complex technical issues methodically.\n\n - Solid understanding of operating systems fundamentals (processes, threads, memory management, concurrency, IPC).\n\n - Experience working in Linux development environments.\n\n - Understanding of computer architecture and interactions between hardware and software systems.\n\n - Strong analytical thinking and ability to break down complex system failures into actionable root causes.\n\n - Ability to work effectively across multiple engineering teams and collaborate in highly technical environments.\n\n - Strong communication skills and willingness to work on ambiguous technical problems.\n\n\n\nPreferred Skills & Qualifications\n\n - Experience building automation frameworks, internal tooling, or test infrastructure\n\n - Familiarity with distributed systems concepts\n\n - Experience debugging large-scale systems or complex infrastructure environments\n\n - Understanding of networking fundamentals and communication between distributed systems\n\n - Experience working with hardware-adjacent software or system integration environments\n\n - Familiarity with performance analysis, system telemetry, and log analysis\n\n - Exposure to production systems validation or infrastructure reliability engineering\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! \n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."}],"apiVersion":"1"}