Cerebras

Senior Hardware Reliability Test Engineer – Electrical Systems & Power Electronics

Sunnyvale, CA. Posted 2 days ago

The role

You will build test setups, fixtures and automation to evaluate the electrical reliability of PCB assemblies and power electronics. You will also investigate electrical failures and work with the Systems, Failure Analysis and Design teams.

What you will do

  • Design, assemble and troubleshoot custom electrical test jigs, fixtures, interface boards, load circuits and wiring harnesses.
  • Work directly with the Systems team to set representative workloads, power sequencing, electrical interfaces and operating limits.
  • Turn product requirements and reliability risks into test plans with stress conditions, sample sizes, durations and acceptance criteria.
  • Build automated test setups with programmable power supplies, electronic loads, switching hardware, sensors and data acquisition equipment.
  • Write Python or equivalent software for instrument control, test sequencing, monitoring, fault capture and analysis.
  • Run accelerated life testing, burn-in, temperature cycling, power/load cycling and biased temperature/humidity testing.
  • Set electrical baselines and monitor changes before, during and after stress.
  • Investigate electrical failures, reproduce system-level anomalies and correlate results with physical failure-analysis findings.
  • Partner with Design, Failure Analysis, Thermal, Quality, Manufacturing and suppliers to validate corrective actions.
  • Document fixture designs, test procedures, results and investigation findings so they can be reproduced.

Required qualifications

  • 5+ years of experience in electrical testing, hardware validation, reliability engineering or electrical failure analysis.
  • Ability to turn electrical test requirements into working lab setups, including custom fixtures, interface circuitry, wiring and instrumentation.
  • Strong knowledge of PCBAs, power conversion, voltage regulation, power distribution and electronic circuit behavior.
  • Practical experience with oscilloscopes, differential and current probes, programmable power supplies, electronic loads, multimeters, power analyzers, source measurement units and data acquisition sys
  • Proficiency in Python, LabVIEW or equivalent tools for test automation and data analysis.
  • Strong circuit-debugging skills and ability to interpret schematics, PCB layouts and component specifications.
  • Understanding of accelerated testing, electronics failure mechanisms, reliability statistics and measurement uncertainty.
  • Familiarity with relevant JEDEC and IPC test methods and qualification practices.
  • Ability to collaborate directly with Systems engineers, communicate technical findings clearly and manage multiple lab investigations.
  • BS in Electrical Engineering, Computer Engineering or a related technical discipline.

Nice to have

  • Master's degree or PhD in Electrical Engineering, Computer Science or a related field.
  • Experience integrating electrical test fixtures with environmental chambers and automated monitoring systems.
  • Hands-on work with high-current power modules, converters and power delivery assemblies.
  • Experience with board bring-up, system integration, embedded firmware, Linux-based test environments and hardware communication interfaces.
  • Knowledge of reliability concerns for power semiconductors, capacitors, magnetic components, connectors and solder joints.
  • Ability to interpret microscopy, thermal imaging, X-ray and cross-sectional findings in the context of electrical failures.

Benefits

  • Possible bonus and equity as part of total compensation.
  • Job stability with startup vitality.
  • Opportunity to publish and open source AI research.
  • Work on one of the fastest AI supercomputers in the world.
  • Simple, non-corporate work culture that respects individual beliefs.

Before you apply

  • Compensation is determined by experience, skills and qualifications.

About the company

Cerebras Systems builds the world's largest AI chip, which the posting says delivers training and inference speeds over 10 times faster than GPU-based cloud services. It works with model labs, global enterprises and AI-native startups, including a multi-year partnership with OpenAI.