Architecture Energy Modeling Engineer - New College Grad 2026
About The Position
NVIDIA is seeking an Architecture Energy Modeling Engineer for its Power Modeling, Methodology and Analysis Team. The team researches, develops, and deploys methodologies to improve product energy efficiency and builds energy models for architectural simulators, RTL simulation, emulation, and silicon platforms. The role focuses on developing machine-learning-based power models to analyze and reduce power consumption in NVIDIA GPUs. The engineer will collaborate with architecture, ASIC design, low-power, performance, software, and physical design teams to develop energy modeling techniques for next-generation GPUs, CPUs, and Tegra SOCs. The work provides early insight into energy consumption for graphics and AI workloads and helps inform architectural, design, and power-management improvements.
Requirements
- Pursuing or recently completed an MS or PhD in Electrical Engineering, Computer Engineering, Computer Science, or equivalent experience.
- Strong coding skills, preferably in Python and C++.
- Background in machine learning, AI, and/or statistical modeling.
- Background in computer architecture and interest in energy-efficient GPU designs.
- Ability to formulate and analyze algorithms and discuss their runtime and memory complexities.
- Basic understanding of energy consumption, estimation, and low-power design.
- Desire to apply quantitative decision-making and analytics to improve product energy efficiency.
- Good verbal and written communication and interpersonal skills.
Nice To Haves
- Familiarity with Verilog and ASIC design principles.
Responsibilities
- Work with architects, designers, and performance engineers to develop an energy-efficient GPU.
- Identify key design features and workloads for machine-learning-based unit power and energy models.
- Develop and own methodologies and workflows for training models using machine-learning and/or statistical techniques.
- Improve trained-model accuracy using different model representations, objective functions, and learning algorithms.
- Develop methodologies to accurately estimate data-movement power and energy.
- Correlate predicted energy from models built at different stages of the design cycle to bridge early estimates to silicon.
- Integrate power and energy models with performance platforms to enable combined performance and power reporting for workloads.
- Develop tools to debug energy inefficiencies in workloads run on silicon, RTL, and architectural simulators, and identify and suggest solutions.
- Prototype new architectural features, build energy models for them, and analyze their system impact.
- Identify, suggest, and/or participate in studies to improve GPU performance per watt.
Benefits
- Equity
- Benefits
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
