Hardware Test Engineer - Silicon Validation
$132,000–$207,000 year
On-siteSanta Clara, California, United States
Job Summary
Oversee the functionality of the Hardware Farm, a unified collection of GPU, SoC, and CPU systems, by performing hardware and software debugs involving PCBs, voltage regulators, OS, drivers, and firmware. Build and maintain FARM regression capabilities and diagnostic infrastructure while authoring test plans, sanity checks, and regression scripts that scale across product lines. Coordinate with global farm and silicon validation teams to ensure system availability, drive critical debugs to closure, and lead the development of automated monitoring and performance analytics. Partner with Farm-Development and location-based PICs to enhance farm processes and translate active debug findings into scalable improvements. Apply AI tools to accelerate log analysis, anomaly detection, and pattern recognition across farm systems.
Required Qualifications
- B.E./B.Tech in ECE or equivalent experience
- 5+ years of experience in the hardware/silicon domain
- In-depth knowledge of various motherboard platforms
- In-depth knowledge of SoCs
- In-depth knowledge of PC hardware and components
- In-depth knowledge of network connections
- Proficiency in Linux OS internals
- Proficiency in scripting (Python, Perl, and TCL)
- Excellent coordination and interpersonal skills to effectively convey technical information and collaborate across global teams
Desired Qualifications
- Use AI tools as a core part of your workflow to explore debug strategies
- Draft test plans using AI tools
- Generate scripts using AI tools
- Build triage flows using AI tools that accelerate log analysis
- Build triage flows using AI tools that accelerate anomaly detection
- Build triage flows using AI tools that accelerate pattern recognition across farm systems
- Apply excellent judgment around AI output
- Know when to trust AI output
- Know when to verify AI output against specs and measurements
- Know when to override AI output
- Share effective prompts, tools, and workflows with the broader team to set the standard on AI-enabled engineering
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