NVIDIA
Power Methodology and Modeling Engineer - New College Grad 2026
$116K–$218K
US, TX, Austin · Full-time · Posted May 5, 2026
- Education
- Pursuing or recently completed an MS or PhD in Electrical or Computer Engineering, or equivalent experience.
About the job
Develop tools, methodologies, and energy models for NVIDIA chips, using workload and design data to improve power efficiency and guide design decisions.
What you'll do
- Build and integrate tools and data flows for power modeling, including data generation, model validation, and connection to performance tools.
- Analyze pre- and post-silicon data to identify bottlenecks and provide feedback to design teams; improve runtime, memory use, and data visualization.
- Experiment with machine learning techniques to evaluate design alternatives and establish power and energy targets.
What they ask for
- Strong coding skills; Python and C++ preferred.
- Ability to formulate and analyze algorithms, including runtime and memory complexity.
- Understanding of VLSI, digital design, and computer architecture.
- Basic understanding of power and energy consumption, estimation, low-power design, and the chip design process from RTL design to tape-out.
Nice to have
- Background in machine learning, AI, and/or statistical modeling.
- Desire to apply quantitative decision-making and analytics to improve energy efficiency.
Pay
116,000 USD - 189,750 USD base salary (Level 2); 136,000 USD - 218,500 USD base salary (Level 3)
Tools
Python, C++, PowerBI, OpenSearch
AI focus
Experiment with machine learning techniques to answer what-if design questions and set power and energy targets for next-generation chips.
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