Reliability Testing Engineer

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.

The Role :

The Reliability Testing Engineer will be responsible for developing, executing, and analyzing reliability test programs to ensure the long-term performance and robustness of complex electronic and electromechanical systems. This role involves hands-on testing across thermal, mechanical, and electrical domains, as well as statistical analysis to characterize product lifetime and identify potential failure mechanisms.

The engineer will design test setups, define stress profiles, manage instrumentation and data collection, and collaborate with cross-functional teams to translate reliability results into actionable design and process improvements. This position requires close interaction with Reliability, Failure Analysis, Design, Quality, and Manufacturing teams.

Responsibilities :

• Develop and execute reliability test plans such as Accelerated Life Testing (ALT), Environmental Stress Screening (ESS), and Highly Accelerated Stress Testing (HAST).
• Design and implement test fixtures, instrumentation setups, and monitoring systems for mechanical, thermal, and electrical reliability experiments.
• Establish test conditions, durations, and sample sizes using physics-of-failure and statistical reliability modeling.
• Perform environmental testing (temperature cycling, humidity, vibration, and pressure) to simulate real-world stresses.
• Configure and monitor data acquisition systems (pressure, temperature, current, flow, etc.) to ensure high-quality test data.
• Conduct failure correlation and root cause analysis in partnership with the Failure Analysis team.
• Apply Weibull and Arrhenius modeling to analyze failure distributions and estimate lifetime metrics (MTTF, MTBF).
• Support design-of-experiment (DOE) studies to validate material, assembly, or design changes for reliability impact.
• Coordinate with vendors and internal teams to ensure test equipment calibration, readiness, and repeatability.
• Document all results, prepare detailed reliability test reports, and present findings to stakeholders.

Skills & Qualifications :

The base salary range for this position is $180,000 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 :

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.

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