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NVIDIA

AI GPU Power Architect

NVIDIA

. Contribute to power estimation models and tools for GPU products and systems such as NVIDIA DGX .

Posted 10/14/2026full-timeUnited StatesMid-LevelSenior💰 $100,000 - $189,750 per yearWebsite

Core Competencies

Role fit
Core Competencies

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Demonstrates expertise in power estimation modeling and energy-efficient design for GPU products, leveraging strong knowledge in Computer Architecture and proficiency in Python for data analysis. Capable of analyzing workload characteristics and implementing machine learning techniques to enhance performance-per-watt metrics.

Highest-signal resume keywords
Power Estimation ModelingComputer ArchitecturePython ProficiencyEnergy Efficient Chip DesignMachine Learning Techniques

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
Power EstimationDigital Logic DesignVLSI DesignData AnalysisPerformance AnalysisEnergy EfficiencyLow Power Design TechniquesDynamic Voltage-Frequency ScalingHigh-Speed InterconnectsGenAI/HPC Workload Analysis
Tools & Technologies
PandasNumPyPyTorch
Industry Keywords
GPU ProductsTCO ImprovementsDatacenter ScalePerformance-per-WattChip Design Fundamentals

Tech Stack

Tools & technologies
NumpyPandasPythonPyTorch

About the role

Key responsibilities & impact
  • Contribute to power estimation models and tools for GPU products and systems such as NVIDIA DGX
  • Explore early GPU and system architecture with a focus on energy efficiency and TCO improvements at GPU and datacenter level
  • Perform performance-versus-power analysis for NVIDIA's future product lineup
  • Deploy machine learning techniques to develop accurate power and performance models of GPUs, CPUs, switches, and platforms
  • Understand workload characteristics for GenAI/HPC workloads at datacenter scale to drive new hardware/software features for performance-per-watt improvements
  • Model and analyze cutting-edge technologies such as high-speed and high-density interconnects

Requirements

What you’ll need
  • Pursuing or recently completed a Bachelor's or Master's in Electrical Engineering, Computer Engineering, or equivalent experience
  • Strong understanding of Computer Architecture and Digital Logic Design/VLSI Design
  • Proficiency with Python and data analysis packages such as Pandas, NumPy, and PyTorch
  • Knowledge of energy efficient chip design fundamentals and related tradeoffs
  • Knowledge of low power design techniques such as multi-VT, clock gating, power gating, and Dynamic Voltage-Frequency Scaling (DVFS)

Benefits

Comp & perks
  • Equity
  • Benefits 📊 Check your resume score for this job Improve your chances of getting an interview by checking your resume score before you apply. Check Resume Score