GPU HW Research Engineer

Qualcomm

Confirmed live 2 days ago Low trust

Quick summary

Work type
On-site
Location
San Diego, CABoxborough, MA
Salary
$161,800–$242,600 / yr
Posted
119 days ago
Freshness
Confirmed live 2 days ago
Closes
Nov 11, 2026

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $205k
This role $202k
$143k most similar roles pay here $253k

This role pays more than 53% of similar roles. Most pay $174,375–$235,750 — the shaded band above. At the midpoint, this role pays about $202k versus about $205k 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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At a glance

TL;DR · GPU HW Research Engineer

The GPU HW Research Engineer joins the GPU Research Team to advance state-of-the-art capabilities in Artificial Intelligence, Machine Learning, and General-Purpose GPU computing. In this role, you will collaborate with architects to design new hardware features and architectural solutions for mobile, Windows on Snapdragon, and data center platforms. You will work with software teams and standardization bodies to influence the evolution of GPU capabilities for large language models and large vision models. The position requires proficiency in C/C++, Python, and APIs such as OpenCL, CUDA, Vulkan, or Direct3D 12. Candidates should possess a strong understanding of GPU memory and cache design, hardware design flows, Verilog or VHDL, and waveform analysis. You will also engage with open-source projects like llama.cpp and vLLM to solve complex problems in ML acceleration and quantization techniques.

What you'll do

  • Design new hardware features to accelerate GPGPU, machine learning, and AI workloads.
  • Develop architectural solutions for mobile, Windows on Snapdragon, and data center GPU platforms.
  • Influence the evolution of GPU capabilities for large language models (LLMs) and large vision models (LVMs).
  • Participate in open-source GPGPU, ML, and AI projects and industry-leading initiatives.
  • Develop and optimize CUDA and OpenCL kernels along with GPU compute shaders.
  • Implement quantization techniques and specialized data types for advanced AI model acceleration.
  • Utilize hardware simulation and emulation tools to perform waveform analysis and design validation.

What we're looking for

  • Bachelor's degree 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.
  • Strong understanding of GPU architectures, programming models, and application domains.
  • Proficiency with APIs such as OpenCL, CUDA, Vulkan, or Direct3D 12.
  • Experience with hardware design flow, Verilog/VHDL, and hardware simulation or emulation tools.
  • Solid programming skills in C/C++ and familiarity with Python.

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