Senior Post Silicon Low Power Integration Engineer

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA

This role focuses on scaling low-power silicon validation and system bring-up for AI and accelerated computing platforms. It involves building intelligent automation, telemetry pipelines, and AI-powered analytics to improve validation coverage, expose power-state issues, and enhance debug workflows. The goal is to improve the power efficiency, stability, and production readiness of NVIDIA products.

What you'd actually do

  1. Define the Power & Performance validation strategy across product lines, including power targets, rail budgets, and low-power feature validation methodologies.
  2. Build intelligent workload characterization frameworks that use telemetry, behavioral clustering, and AI-assisted analytics to improve validation coverage and expose power-state and data-path issues earlier in the development cycle.
  3. Define the instrumentation, counters, telemetry frameworks, and firmware hooks needed to support scalable silicon observability, automated validation, and AI-powered debug workflows prior to tapeout.
  4. Bring up and validate system-level low-power features across pre-silicon and post-silicon environments using sophisticated automation, data-driven validation methodologies, and generative AI-assisted debug techniques.
  5. Develop AI/ML-assisted infrastructure for telemetry analysis, anomaly detection, predictive validation analytics, workload optimization, automated triage, and cross-generation debug correlation.

Skills

Required

  • BS/MS in EE, CE, CS, Systems Engineering, or equivalent experience.
  • 10+ years of experience in silicon characterization, low-power feature validation, system integration, or post-silicon productization.
  • Strong understanding of silicon power behavior, Windows/Linux low-power states, firmware interactions, power/performance tradeoffs, and system-level validation methodologies.
  • Experience building scalable automation, telemetry analytics, or AI-assisted engineering workflows for silicon validation, debug, or productization.
  • Strong EE fundamentals, including digital design, computer architecture, power analysis, statistics, and scripting/programming skills.
  • Hands-on experience with silicon bring-up, lab validation, debug methodologies, and hardware lab instrumentation.
  • Familiarity with AI/LLM-assisted engineering workflows, intelligent automation frameworks, telemetry analytics, or data-driven debug infrastructure.

Nice to have

  • Experience applying AI/ML or LLM technologies to silicon validation, telemetry analytics, workload optimization, or debug automation.
  • Background in platform power management technologies such as S0ix, ASPM, RTD3, Memory Self Refresh, or system-level power-state coordination.
  • Experience building large-scale telemetry pipelines, automated validation dashboards, or intelligent observability infrastructure.
  • Strong Python, data analytics, and automation framework development experience.
  • Experience working across architecture, firmware, silicon validation, and manufacturing organizations to drive production readiness.

What the JD emphasized

  • AI-powered analytics
  • intelligent automation
  • telemetry pipelines
  • modern debug workflows
  • AI/ML-assisted infrastructure
  • AI/LLM-assisted engineering workflows
  • AI/ML or LLM technologies to silicon validation