Power Methodology and Modeling Engineer — New College Grad 2026

Job Title

Power Methodology and Modeling Engineer — New College Grad 2026

Role Summary

Member of the Architecture Energy Modeling team responsible for developing tools, methodologies, and models to measure and improve energy usage for NVIDIA GPUs, CPUs and Tegra SoCs. The role collaborates with architecture, ASIC design, low-power, performance, software, and physical design teams to integrate power models into design and performance flows.

This position focuses on energy modeling, data pipeline and tooling, correlation of metrics, and providing analysis that informs architecture and design trade-offs.

Experience Level

Entry-level / New college graduate. Targeted at recent or soon-to-be graduates (MS or PhD) and candidates with equivalent practical experience; approximately 0–2 years of professional experience.

Responsibilities

The primary responsibilities involve building tooling and workflows to generate, sanitize, integrate, analyze, store, and visualize power and energy data for chips.

• Define and implement tools and methodologies to generate data from post-layout netlists for data-movement power analytical models.
• Develop infrastructure to sanitize model metrics to improve correlation accuracy.
• Integrate power models with performance tools and flows.
• Identify and address runtime and memory limitations in existing flows to accelerate model delivery.
• Mine pre- and post-silicon performance data to identify critical data paths and bottlenecks; provide feedback to design teams to improve power efficiency.
• Collaborate with floorplan, performance, verification, and emulation methodology teams to integrate data-movement power models.
• Experiment with ML techniques to answer what-if design questions and set power/energy targets.
• Enable efficient storage and retrieval of model and measurement data in databases and support visualization using platforms such as PowerBI or OpenSearch.

Requirements

Core technical skills and experience required or strongly preferred.

• Strong coding skills, preferably Python and C++.
• Ability to formulate and analyze algorithms, including reasoning about runtime and memory complexity.
• Understanding of VLSI, digital design, and computer architecture concepts.
• Basic understanding of power and energy consumption, estimation, and low-power design techniques.
• Basic understanding of the chip design flow from RTL to tape-out.
• Experience or interest in building data pipelines, database-backed storage, and data visualization solutions.
• Ability to collaborate across architecture, design, verification, and tooling teams and to present quantitative analysis to influence design decisions.
• Nice-to-have: background in machine learning, AI, or statistical modeling.

Education Requirements

Pursuing or recently completed a MS or PhD in Electrical Engineering or Computer Engineering, or equivalent practical experience.

About the Company

Company: NVIDIA

Headquarters: Santa Clara, California, USA

NVIDIA is a global leader in accelerated computing, renowned for its innovative solutions in AI and digital twins that transform diverse industries. The company specializes in networking technologies, providing end-to-end InfiniBand and Ethernet solutions for servers and storage that optimize performance and scalability. NVIDIA serves sectors such as high-performance computing, enterprise data centers, and cloud computing, constantly reinventing its products and services to stay ahead in the market.