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 top 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.
Thanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, 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 Systems Inc. has multiple openings for Sr. Technical Staff.
Title: Sr. Technical Staff
Job Duties:
- 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 wafers 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 to 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 that 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 FPGA’s, power and cooling, and apply that knowledge to the debug of silicon features.
- Development of debug tools in Python to program and analyze the behavior of the Wafer Scale Engine.
- Development of 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.
- Documentation of issues found, tools and flow.
Minimum Requirements:
Master’s degree or foreign equivalent degree in Electrical Engineering, Computer Engineering, or a related field and 3 years of experience as Application Engineer, Sr. Technical Staff, Hardware Engineer, or a related occupation required.
Required Skills:
- Electrical Signal Integrity Analysis;
- Hardware Bring-up & Debug;
- Functional and Electrical characterization;
- Test automation using scripting language; and
- High Speed Interfaces & Protocols including Ethernet, CPRI, or Interlaken.
Additional Information:
Employer’s name: Cerebras Systems Inc.
Job site : 1237 E Arques Avenue, Sunnyvale, CA 94085
Telecommuting permitted.
Salary Range: $250,000.00 per year to $275,000.00 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 # 145 on resume or cover letter.
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 2026.
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.
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Skills Required
- Master's degree in Electrical Engineering, Computer Engineering, or a related field
- 3 years of experience as Application Engineer, Sr. Technical Staff, or Hardware Engineer
- 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
What We Do
Cerebras Systems is a team of pioneering computer architects, computer scientists, deep learning researchers, functional business experts and engineers of all types. We have come together to build a new class of computer to accelerate artificial intelligence work by three orders of magnitude beyond the current state of the art. The CS-2 is the fastest AI computer in existence. It contains a collection of industry firsts, including the Cerebras Wafer Scale Engine (WSE-2). The WSE-2 is the largest chip ever built. It contains 2.6 trillion transistors and covers more than 46,225 square millimeters of silicon. The largest graphics processor on the market has 54 billion transistors and covers 815 square millimeters. In artificial intelligence work, large chips process information more quickly producing answers in less time. As a result, neural networks that in the past took months to train, can now train in minutes on the Cerebras CS-2 powered by the WSE-2. Join us: https://cerebras.net/careers/
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