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Architecture Energy Modeling Engineer - New College Grad 2026

NVIDIA· Engineer, ASIC
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Santa Clara, CA$116k - $189.8kfull-timePosted 1mo ago

About the role

Architecture Energy Modeling Engineer to join the Power Modeling, Methodology and Analysis Team. Focus on developing ML-based power/energy models, integrating into architectural simulators, RTL simulation, emulation and silicon platforms, to improve GPU energy efficiency.

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 their platforms to enable combined reporting of performance and power for various workloads.
  • Develop tools to debug energy inefficiencies observed in various workloads run on silicon, RTL, and architectural simulators. Identify and suggest solutions to fix the energy inefficiencies.
  • Prototype new architectural features, build an energy model for those new features, and analyze the system impact.
  • Identify, suggest, and/or participate in studies for improving GPU perf/watt.

Qualifications

  • Pursuing or recently completed a MS or PhD in Electrical Engineering, Computer Engineering, Computer Science or equivalent experience.
  • Strong coding skills, preferably in Python, 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 our products.
  • Good verbal/written communication and interpersonal skills.

Skills

Required:PythonC++Machine Learning / Statistical Modeling

Benefits

  • equity
  • benefits (see company benefits)
Last updated Aug 28, 2026. Interested? Apply on the company site.

About NVIDIA

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NVIDIA invents the GPU and drives advances in AI, HPC, gaming, creative design, autonomous vehicles, and robotics.

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