Senior Power Analysis and Optimization Engineer

Nvidia

Quick summary

Work type
On-site
Location
Santa Clara, CA · Austin, TX
Salary
$136,000–$218,500 / yr
Posted
15 days ago

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Competitive pay

How this pay compares to similar roles

Similar $188k
This role $177k
$126k most similar roles pay here $228k

This role pays more than 53% of similar roles. Most pay $159,937–$216,250 — the shaded band above. At the midpoint, this role pays about $177k versus about $188k for comparable roles.

Based on 240 similar postings.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 563 open roles on FindRole.

Listed pay typically runs $168,000–$264,500 across 556 roles with salary data.

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At a glance

TL;DR · Senior Power Analysis and Optimization Engineer

As a Senior Power Architecture & Optimization Engineer at NVIDIA, you will join a cutting-edge team focused on developing the most energy-efficient GPUs and SoCs. Your daily responsibilities include analyzing full-chip and unit-level power data using advanced tools like PowerArtist and PrimePower, translating insights into design improvements, and developing ML/RL-based models for anomaly detection and dynamic power management. You’ll also train large language models to assist engineers in interpreting complex power data and recommending optimizations. Key skills required are a strong background in energy consumption and low-power design, proficiency in Verilog and ASIC principles, coding expertise in Python, Perl, and C++, and experience with machine learning and reinforcement learning applied to EDA and system-level optimization. This role is pivotal in shaping the future of NVIDIA’s power architecture through innovative AI-driven solutions.

What you'll do

  • Analyze full-chip and unit-level power using advanced tools to identify design improvements.
  • Develop and deploy ML/RL-based models for dynamic power management and anomaly detection.
  • Train LLMs to assist engineers in interpreting complex power data and proposing optimizations.
  • Conduct comparative power analysis across workloads to uncover optimization opportunities.
  • Prototype new architectural features focusing on their energy implications using Verilog.
  • Automate power analysis flows with Python, Perl, and C++ to enhance efficiency.
  • Apply AI techniques to recommend or automatically tune power-efficient design configurations.

What we're looking for

  • MS (or equivalent) in EE/CE/CS with 5+ years or PhD with 3+ years of relevant experience.
  • Strong expertise in energy consumption, power estimation, data movement, and low-power design principles.
  • Proficiency in Verilog and hands-on experience with ASIC design tools like PowerArtist and PrimePower.
  • Solid coding skills in Python, Perl, and C++ for automation and scaling power analysis flows.
  • Experience or strong interest in applying machine learning, reinforcement learning, and data analytics to EDA and system-level optimization.
  • Familiarity with building and using LLMs as engineering copilots for EDA/power/architecture workflows.

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