GPU HW Research Engineer

Qualcomm

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Quick summary

Work type: On-site
Location: Boxborough, MASan Diego, CA
Salary: $169,500–$254,300 / yr
Posted: 40 days ago
Freshness: Confirmed live today
Closes: Mar 16, 2027
Nearby: 99+ roles within 25 mi

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Competitive pay

How this pay compares to similar roles

Similar $207k

This role $212k

$140k $267k

below market most similar roles pay here above market

This role pays more than 57% of similar roles. Most pay $177,250–$236,487 — the blue band above. At the midpoint, this role pays about $212k versus about $207k for comparable roles.

Based on 240 similar postings.

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About Qualcomm

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

Qualcomm currently has 575 open roles on FindRole.

Listed pay typically runs $147,900–$221,900 across 550 roles with salary data.

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At a glance

TL;DR · GPU HW Research Engineer

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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. You will collaborate with architects to design new hardware features and architectural solutions for mobile, Windows on Snapdragon, and data center GPUs. Your daily work involves enhancing architectures for accelerating GPGPU, ML, and AI workloads, including large language models and large vision models. You will utilize skills in C/C++, Python, and hardware design flows involving Verilog or VHDL. The role requires proficiency with APIs such as OpenCL, CUDA, Vulkan, or Direct3D 12, alongside experience in hardware simulation, waveform analysis, and GPU memory and cache design hierarchy. You will also contribute to open-source projects and industry-leading initiatives.

Skills

GPU Architecture CUDA OpenCL C++ Python Vulkan Direct3D 12 Verilog VHDL llama.cpp vLLM Hardware Simulation Waveform Analysis Quantization ML AI GPGPU

What you'll do

Design new hardware features and enhance existing GPU architectures for GPGPU, ML, and AI workloads.
Develop architectural solutions for mobile, Windows on Snapdragon, and data center GPU platforms.
Work with software and hardware teams to deliver cutting-edge GPU solutions.
Participate in and contribute to open-source GPGPU, ML, and AI projects.
Influence GPU capabilities for large language models (LLMs) and large vision models (LVMs).
Optimize CUDA and OpenCL kernels and GPU compute shaders.
Design GPU hardware features specifically for ML and AI acceleration.

What we're looking for

Bachelor's degree in a related field and 4+ years of relevant engineering experience.
Master's degree in a related field and 3+ years of relevant engineering experience.
PhD in a related field and 2+ years of relevant engineering experience.
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 and basic knowledge of Verilog or VHDL.
Solid programming skills in C/C++.
Familiarity with Python (preferred).

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