Power Methodology and Modeling Engineer – New College Grad 2026

Join NVIDIA's Architecture Energy Modeling Team to collaborate with various engineering teams in studying and implementing energy modeling techniques for next-generation GPUs, CPUs, and Tegra SOCs. Your work will focus on understanding energy usage in graphics and AI workloads, contributing to improvements in architecture, design, and power management.

Responsibilities:

• Define and implement tools and methodologies for efficient data generation from post layout netlists for power analytical models.
• Develop tools and infrastructure to sanitize metrics for high correlation accuracy.
• Integrate power models with performance tools efficiently.
• Identify runtime and memory limitations in existing flows to expedite model delivery.
• Analyze pre- and post-silicon performance data to identify bottlenecks and provide feedback for power efficiency improvements.
• Collaborate with various teams to integrate data movement power models.
• Experiment with ML techniques to set power/energy targets for next-gen chips.
• Enable efficient data storage and retrieval from databases.
• Facilitate data visualization using platforms like PowerBI and OpenSearch.

Qualifications:

• Pursuing or recently completed a BS, MS, or PhD in Electrical or Computer Engineering or equivalent experience.
• Strong coding skills, preferably in Python or C++.
• Ability to analyze algorithms and their runtime and memory complexities.
• Understanding of VLSI, digital design, and computer architecture concepts.
• Basic knowledge of power and energy consumption estimation and low power design.
• Familiarity with the chip design process from RTL design to tape-out.
• Background in machine learning, AI, or statistical modeling is a plus.

Skills:

• Quantitative decision-making and analytics for energy efficiency improvement.
• Strong problem-solving and analytical skills.
• Collaboration and communication skills to work with diverse teams.