Cerebras Systems
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Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs.
Cerebras' current customers include global corporations across multiple industries, national labs, and top-tier healthcare systems. In January, we announced a multi-year, multi-million-dollar partnership with Mayo Clinic, underscoring our commitment to transforming AI applications across various fields. In August, we launched Cerebras Inference, the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services.
Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs.
Cerebras' current customers include global corporations across multiple industries, national labs, and top-tier healthcare systems. In January, we announced a multi-year, multi-million-dollar partnership with Mayo Clinic, underscoring our commitment to transforming AI applications across various fields. In August, we launched Cerebras Inference, the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services.
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. Read our blog:Five Reasons to Join Cerebras in 2025. 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.
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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. Read our blog:Five Reasons to Join Cerebras in 2025. 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.
Seniority level
Seniority level Entry level Employment type
Employment type Full-time Job function
Job function Engineering and Information Technology Referrals increase your chances of interviewing at Cerebras Systems by 2x Sign in to set job alerts for “Engineer” roles.
Mountain View, CA $94,050.00-$141,550.00 4 days ago Mechanical Manufacturing Engineer, Data Centers
Sunnyvale, CA $96,000.00-$138,000.00 1 week ago Sunnyvale, CA $170,000.00-$240,000.00 1 week ago Sunnyvale, CA $139,000.00-$200,000.00 1 week ago Palo Alto, CA $168,000.00-$179,000.00 2 weeks ago Sunnyvale, CA $111,000.00-$164,000.00 1 week ago Fremont, CA $139,000.00-$200,000.00 2 days ago Mountain View, CA $181,000.00-$297,000.00 1 week ago Manufacturing Engineer, Product Operations
Sunnyvale, CA $138,000.00-$202,000.00 1 week ago Mechanical Product Design Engineer, Platforms, University Graduate
Sunnyvale, CA $105,000.00-$151,000.00 1 week ago Fremont, CA $147,000.00-$208,000.00 2 weeks ago Mountain View, CA $138,225.00-$207,575.00 2 weeks ago Fremont, CA $70,000.00-$110,000.00 3 weeks ago Mountain View, CA $92,000.00-$136,000.00 2 days ago Product Design Mechanical Engineer, Reality Labs
Sunnyvale, CA $204,000.00-$281,000.00 2 weeks ago San Jose, CA $130,000.00-$160,000.00 1 day ago San Jose, CA $115,000.00-$135,000.00 1 week ago Sunnyvale, CA $144,000.00-$211,000.00 1 week ago We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.
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