Senior Architecture Energy Modeling Engineer

at Nvidia
USD 168,000-310,500 per year
SENIOR
✅ On-site

SCRAPED

Used Tools & Technologies

Not specified

Required Skills & Competences ?

Python @ 7 Algorithms @ 4 Machine Learning @ 4 Communication @ 4 Reporting @ 4 GPU @ 4

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 role focuses on building energy and power models that integrate into architectural simulators, RTL simulation, emulation, and silicon platforms, and on developing machine learning–based power models to analyze and reduce GPU power consumption. You will be a member of the Power Modeling, Methodology and Analysis Team and collaborate with Architects, ASIC Design Engineers, Low Power Engineers, Performance Engineers, Software Engineers, and Physical Design teams.

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 using 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.
  • 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 on silicon, RTL, and architectural simulators; identify and propose solutions.
  • Prototype new architectural features, build energy models for those features, and analyze system impact.
  • Identify, suggest, and/or participate in studies to improve 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 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 and written communication and interpersonal skills.

Benefits and Additional Information

  • Base salary ranges by level:
    • Level 4: 168,000 USD - 264,500 USD
    • Level 5: 196,000 USD - 310,500 USD
  • You will also be eligible for equity and benefits (see NVIDIA benefits page).
  • Applications for this job will be accepted at least until September 8, 2025.
  • NVIDIA is an equal opportunity employer committed to fostering a diverse work environment.