Senior Architecture Energy Modeling Engineer

Details

We are looking for a Senior Architecture Energy Modeling Engineer to research, develop, and deploy methodologies that improve energy efficiency of NVIDIA products. The team builds energy models that integrate into architectural simulators, RTL simulation, emulation and silicon platforms, and develops machine-learning-based power models to analyze and reduce power consumption of NVIDIA GPUs, CPUs and Tegra SoCs.

Responsibilities

• Collaborate with architects, ASIC design engineers, low power engineers, performance engineers, software engineers, and physical design teams to develop energy-efficient GPUs and SoCs.
• 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 model accuracy via different model representations, objective functions, and learning algorithms.
• Develop methodologies to estimate data-movement power/energy accurately.
• Correlate predicted energy from models built at different stages of the design cycle to bridge early estimates to silicon.
• Integrate power/energy models into performance infrastructure to enable combined reporting of performance and power for workloads.
• Develop tools to debug energy inefficiencies observed on silicon, RTL, and architectural simulators; identify and suggest fixes.
• Prototype new architectural features, build energy models for those features, and analyze system impact.
• Identify, suggest, and/or participate in studies for improving GPU perf/watt.

Requirements

• MS (or equivalent experience) or PhD in a related field.
• 6+ years of 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 runtime and memory complexity.
• Basic understanding of fundamental concepts 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 skills.

Compensation & Benefits

• Base salary range (Level 4): 168,000 USD - 264,500 USD per year.
• Base salary range (Level 5): 196,000 USD - 310,500 USD per year.
• Eligible for equity and benefits (see https://www.nvidia.com/en-us/benefits/).

Other details

• Applications accepted at least until April 14, 2026.
• NVIDIA uses AI tools in its recruiting processes.
• NVIDIA is an equal opportunity employer and values diversity.