AI GPU Power Architect

Nvidia

Confirmed live today High trust

Quick summary

Work type
On-site
Location
Santa Clara, CA
Salary
$100,000–$166,750 / yr
Employment
Full-time
Posted
13 days ago
Freshness
Confirmed live today

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $201k
This role $133k
$81k $273k
below market most similar roles pay here above market

This role pays less than 91% of similar roles. Most pay $166,200–$235,750 — the blue band above. At the midpoint, this role pays about $133k versus about $201k for comparable roles.

Based on 240 similar postings.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 1623 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 1110 roles with salary data.

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At a glance

TL;DR · AI GPU Power Architect

The AI GPU Power Architect - New College Grad 2026 joins the Applied Power Architecture team to develop state of the art GPUs for AI, HPC, Automotive, GeForce, and Mobile products. This role involves contributing to power estimation models and tools for GPU products and systems like NVIDIA DGX. Key responsibilities include early architecture exploration focusing on energy efficiency and TCO improvements, performing performance versus power analysis, and deploying machine learning techniques to develop accurate models for GPUs, CPUs, and switches. You will analyze workload characteristics for GenAI and HPC at datacenter scale to drive hardware and software features. Required skills include knowledge of computer architecture, digital logic design, and VLSI design. Proficiency in Python, Pandas, NumPy, and PyTorch is necessary to model high-speed interconnects and low-power design techniques.

What you'll do

  • Contribute to power estimation models and tools for GPU products and systems like NVIDIA DGX.
  • Conduct early GPU and system architecture exploration focusing on energy efficiency and TCO improvements.
  • Perform performance versus power analysis for future product lineups.
  • Deploy machine learning techniques to develop accurate power and performance models for GPUs, CPUs, and switches.
  • Analyze workload characteristics for GenAI and HPC workloads at datacenter scale to drive hardware and software features.
  • Model and analyze cutting-edge technologies such as high-speed and high-density interconnects.

What we're looking for

  • 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 like 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).

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