Senior Power Analysis and Optimization Engineer

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA +1

Senior Engineer to apply AI/ML and LLMs to power analysis and optimization for NVIDIA's GPUs and SoCs. Focus on developing and productionizing ML/RL models and custom LLMs to improve energy efficiency, interpret power data, and recommend optimizations. Involves RTL analysis, Verilog prototyping, and automation.

What you'd actually do

  1. Develop and productionize power‑aware models and flows, including ML/RL‑based techniques for anomaly detection, dynamic power management, and design‑space exploration.
  2. Design and train new LLMs that “learn the art” of power analysis from design data, power reports, bug histories, and best practices—so they can: Assist engineers in interpreting complex power data, Propose likely root causes and candidate fixes, Recommend architectural and micro‑architectural optimizations for power
  3. Apply AI to power optimization: build and deploy data‑driven models—using machine learning, reinforcement learning, data analytics, and custom LLMs—to recommend or automatically tune power‑efficient configurations and policies.
  4. Automate and scale flows (Python/Perl/C++), and define new pipelines that fast‑track power anomaly detection and close the loop between power data, AI models, and design decisions.
  5. Partner closely with Architects, Performance, Software, ASIC Design, and Physical Design teams to interpret power data, root‑cause power bugs, and drive fixes and design changes.

Skills

Required

  • MS (or equivalent experience) and 5yrs experience OR PHD + 3yr experience in EE/CE/CS or related fields.
  • Strong understanding of energy consumption, power estimation, data movement, and low‑power design.
  • Familiarity with Verilog and ASIC design principles, and hands‑on experience with tools such as PowerArtist, PrimePower/PrimePower RTL, RTL Architect, or similar.
  • Solid coding and automation skills, preferably in Python, Perl, and C++.
  • Experience or strong interest in machine learning, reinforcement learning, and data analytics, ideally applied to EDA, architecture, or system‑level optimization.
  • Interest or experience in building and using LLMs or other foundation models as engineering copilots—especially for EDA/power/architecture workflows.

Nice to have

  • Excellent communication and collaboration skills to work effectively with cross‑functional design and architecture teams.
  • A genuine desire to bring data‑driven, AI‑assisted decision‑making into power architecture and help shape the energy profile of NVIDIA’s future products.

What the JD emphasized

  • productionize power‑aware models and flows
  • productionize ML/RL models
  • build and deploy data-driven models
  • productionize AI/LLM models

Other signals

  • AI/ML for power analysis
  • LLMs for power optimization
  • ML/RL for anomaly detection and power management
  • Productionizing ML/RL models