Sr. Technical Staff

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.

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