Senior Power Analysis and Optimization Engineer
NVIDIA· Engineer, ASIC
Hybrid (Santa Clara, CA), Hybrid (Austin, TX)$136k - $218.5k + equityFull-timePosted 7mo ago
About the role
Senior Power Architecture & Optimization Engineer focusing on energy efficiency using analytics, AI, ML/RL, data analytics, and large language models to model, analyze, and optimize energy consumption across full-chip and unit-level designs for NVIDIA GPUs and Tegra SoCs.
Responsibilities
- Analyze full-chip and unit-level power using RTL and gate-level power tools and translate data into design/architectural improvements.
- Develop and productionize power-aware models and flows, including ML/RL-based techniques for anomaly detection, dynamic power management, and design-space exploration.
- Design and train new LLMs that learn power analysis from design data, power reports, bug histories, and best practices to assist engineers, propose root causes and fixes, and recommend optimizations.
- Perform comparative power analysis across workloads, products, and design options to identify trends, anomalies, and optimization opportunities.
- Partner with Architects, Performance, Software, ASIC Design, and Physical Design teams to interpret power data and drive fixes.
- Prototype and evaluate new architectural features in Verilog with focus on power/energy implications.
- Automate and scale flows (Python/Perl/C++) and define pipelines that accelerate power anomaly detection and link power data, AI models, and design decisions.
- Apply AI to power optimization by building/deploying data-driven models to recommend or tune power-efficient configurations and policies.
Qualifications
- MS (or equivalent) and 5 years of experience OR PhD + 3 years 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.
- Excellent communication and collaboration skills for cross-functional work.
- Desire to bring data-driven, AI-assisted decision-making into power architecture and influence NVIDIA’s energy profile.
Skills
Required:Power analysis and estimationVerilogPower design toolsProgramming and automationMachine learning / reinforcement learningCommunication and collaboration
Nice to have:LLMs / foundation models for engineering copilots
Benefits
- equity
- benefits (as per company listing)
Last updated Oct 23, 2026. Interested? Apply on the company site.
About NVIDIA
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