GPU Power Analysis Engineer

Qualcomm

Confirmed live 2 days ago Low trust

Quick summary

Work type
On-site
Location
San Diego, CA
Salary
$161,800–$242,600 / yr
Posted
123 days ago
Freshness
Confirmed live 2 days ago
Closes
Nov 7, 2026

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $206k
This role $202k
$150k most similar roles pay here $254k

This role pays more than 50% of similar roles. Most pay $177,250–$235,750 — the shaded band above. At the midpoint, this role pays about $202k versus about $206k for comparable roles.

Based on 240 similar postings.

Employer

About Qualcomm

Qualcomm is a leading American semiconductor and telecommunications company based in San Diego, CA.

Qualcomm currently has 623 open roles on FindRole.

Listed pay typically runs $148,300–$222,500 across 603 roles with salary data.

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View all roles at Qualcomm

At a glance

TL;DR · GPU Power Analysis Engineer

As a GPU Power Analysis Engineer within the Graphics System Team, you will contribute to the development of next-generation graphics processing units and compute devices. You will perform performance and power efficiency analysis at both the GPU and system levels for graphics and AI workloads, such as games and benchmarks. Your daily work involves identifying architectural, hardware, and software improvements by analyzing silicon measurements and utilizing various technical knobs to optimize performance per watt. You will also develop tools for streamlined debug tasks and establish scalable methodologies for power projections during sizing. The role requires expertise in GPU and SoC micro-architecture, power concepts, and signal processing techniques. Required skills include strong Python programming, proficiency with AI tools for debugging, and a deep understanding of components like CPUs, DDR paths, and graphics APIs to solve complex system-level problems.

What you'll do

  • Perform performance and power efficiency modeling for GPU and system-level graphics and AI workloads.
  • Identify hardware and software optimization opportunities to improve performance per watt.
  • Establish scalable methodologies for power projections during next-generation GPU and SoC sizing.
  • Conduct competitive analysis of benchmarks and games to identify architectural gaps and improvement opportunities.
  • Develop tools to streamline and scale debug and validation tasks.
  • Incorporate post-silicon learning into the development of next-generation models.

What we're looking for

  • Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, or a related field.
  • Master's degree or PhD in Computer Engineering, Computer Science, Electrical Engineering, or a related field.
  • 4+ years of experience in Software, Hardware, or Systems Engineering with a Bachelor's degree.
  • 3+ years of experience in Software, Hardware, or Systems Engineering with a Master's degree.
  • 2+ years of experience in Software, Hardware, or Systems Engineering with a PhD.
  • Understanding of GPU/SoC architecture and common hardware blocks like Display, CPU, and BUS.
  • Strong knowledge of Python or other programming languages and proficiency in using AI tools for coding and debugging.
  • Experience in power analysis at the micro-architecture and system levels, including post-si debugging.

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