Architecture Energy Modeling Engineer - New College Grad 2025

Details

Today, NVIDIA is tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, encouraging environment where everyone is inspired to do their best work.

We are looking for an Architecture Energy Modeling Engineer to join the Power Modeling, Methodology and Analysis Team. The team researches, develops, and deploys methodologies to help NVIDIA's products become more energy efficient and builds energy models that integrate into architectural simulators, RTL simulation, emulation and silicon platforms. Key work includes developing Machine Learning based power models to analyze and reduce power consumption of NVIDIA GPUs and collaborating with architects, ASIC design, low power, performance, software and physical design teams to influence architectural and power management improvements.

Responsibilities

• Work with architects, designers, and performance engineers to develop an energy-efficient GPU.
• Identify key design features and workloads for building Machine Learning based unit power/energy models.
• Develop and own methodologies and workflows to train models using ML and/or statistical techniques.
• Improve the accuracy of trained models by using different model representations, objective functions, and learning algorithms.
• Develop methodologies to estimate data movement power/energy accurately.
• Correlate the predicted energy from models built at different stages of the design cycle, with the goal of bridging early estimates to silicon.
• Work with performance infrastructure teams to integrate power/energy models into platforms to enable combined reporting of performance and power for workloads.
• Develop tools to debug energy inefficiencies observed in workloads run on silicon, RTL, and architectural simulators; identify and suggest solutions.
• Prototype new architectural features, build an energy model for those features, and analyze system impact.
• Identify, suggest, and/or participate in studies for improving GPU perf/watt.

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.
• Familiarity with Verilog and ASIC design principles is a plus.
• Ability to formulate and analyze algorithms, and comment on their runtime and memory complexities.
• Basic understanding of fundamental concepts of energy consumption, estimation, and low power design.
• Desire to bring quantitative decision-making and analytics to improve the energy efficiency of products.
• Good verbal/written communication and interpersonal skills.

Compensation & Benefits

• Base salary ranges provided by level:
  • Level 2: 108,000 USD - 184,000 USD
  • Level 3: 136,000 USD - 212,750 USD
• Eligible for equity and benefits (link to NVIDIA benefits referenced in original posting).

Additional Information

• Applications accepted at least until November 17, 2025.
• NVIDIA is an equal opportunity employer and values diversity. The company does not discriminate on the basis of protected characteristics.