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Post-Silicon Validation and Methodology Engineer

NVIDIA· Engineer, ASIC
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Santa Clara, CA$136k - $218.5kFull-timePosted 4mo ago

About the role

Hardware engineer focused on bring-up, validation, and methodology for next-generation silicon. Develops test infrastructure, AI-assisted lab workflows, and coverage strategies to find issues before software is production-ready, improving velocity across silicon programs.

Responsibilities

  • Own bring-up, validation, qualification, tuning, and productization plans for next-generation silicon — from first power-on through PVT sign-off.
  • Partner across architecture, build, firmware, and software teams to define requirements for power management and clocking features, then drive coverage from pre-silicon through production.
  • Build and deploy AI assisted lab workflows to automate bring-up telemetry and silicon measurement data evaluation, provide anomaly detection on regression results, and support debug-triage tooling.
  • Build the test infrastructure, characterization methodologies, and bring-up playbooks to shift post-silicon coverage left and raise velocity across programs.
  • Lead root-cause analysis on HW/SW interaction issues with measurement field, instrumentation judgment, and hypothesis rigor to close them under schedule pressure.
  • Identify where current processes break and redesign them (bring-up sequencing, debug forums, regression frameworks, lab metrics) to ensure continuous improvement.

Qualifications

  • BS or MS in Electrical or Computer Engineering (or equivalent experience), plus 5+ years in silicon bring-up, validation, debug, or productization.
  • Deep fundamentals across digital development, microarchitecture, timing, clocking, power, noise, and control systems, with ability to reason across HW/SW boundary in lab constraints.
  • Hands-on lab proficiency: oscilloscopes, logic analyzers, power analyzers, and ability to pick the right instrument for bring-up questions.
  • Strong programming and scripting proficiency: Python, C/C++; experience building lab automation or test infrastructure adopted by others, not just personal scripts.
  • Proficiency in using AI tools to accelerate silicon validation: automated analysis of bring-up logs, regression data, or lab instrumentation output; anomaly detection on silicon datasets; or LLM-assisted debug triage (with awareness of when measurement must remain manual).

Skills

Required:Bring-up and validation planningHW/SW boundary reasoningLab instrumentationScripting and automation
Nice to have:AI-assisted validation

Benefits

  • equity
  • benefits package
  • competitive salaries and comprehensive benefits package
Last updated Oct 16, 2026. Interested? Apply on the company site.

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