Architecture Energy Modeling Engineer - New College Grad 2026

Job Title

Architecture Energy Modeling Engineer - New College Grad 2026

Role Summary

Join NVIDIA's Power Modeling, Methodology and Analysis Team to develop energy and power models for GPUs, CPUs, and SoCs. The role focuses on building machine-learning and statistical models that estimate unit and system energy consumption across architectural simulators, RTL, emulation, and silicon.

Work closely with architects, ASIC designers, low-power engineers, performance teams and software engineers to influence architectural and design decisions that improve energy efficiency.

Experience Level

Entry-level. Targeted at new college graduates (MS or PhD) or candidates with equivalent practical experience; typical experience: 0–3 years.

Responsibilities

Primary responsibilities include building models, integrating them into analysis platforms, and using model-driven analysis to improve GPU energy efficiency.

• Identify key design features and representative workloads for energy modeling.
• Develop machine-learning and statistical unit power/energy models and associated training workflows.
• Improve model accuracy via different representations, loss functions, and learning algorithms.
• Estimate data-movement power/energy and correlate estimates across design stages (early architecture → RTL → silicon).
• Integrate power/energy models into performance and simulation platforms for combined reporting.
• Develop tools to debug energy inefficiencies observed on silicon, RTL, and simulators and propose fixes.
• Prototype architectural features, build energy models for them, and evaluate system-level perf/watt impact.
• Collaborate across teams to influence design and power-management improvements.

Requirements

Must-have skills and experiences for success in this role.

• Must-have: Strong programming skills (Python preferred; C++ experience desirable).
• Must-have: Background in machine learning, AI, or statistical modeling and experience applying those techniques to modeling or analysis tasks.
• Must-have: Familiarity with computer architecture and an interest in energy-efficient GPU/SoC design.
• Must-have: Ability to formulate and analyze algorithms, including runtime and memory complexity.
• Must-have: Basic understanding of energy consumption, estimation techniques, and low-power design concepts.
• Must-have: Good verbal and written communication and the ability to work cross-functionally.
• Nice-to-have: Familiarity with Verilog and ASIC design principles.
• Nice-to-have: Experience integrating models into simulators, RTL flows, emulation, or silicon platforms; experience with performance infrastructure.

Education Requirements

Pursuing or recently completed an MS or PhD in Electrical Engineering, Computer Engineering, Computer Science, or a related technical field, 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.