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GPU HW Research Engineer

Qualcomm
September 04, 2026
Full-time
On-site
Boxborough, Massachusetts, United States
$161,800 - $242,600 USD yearly
SoC Architecture Jobs, Level - Mid-Career

Job Title

GPU HW Research Engineer

Role Summary

Design and architect GPU hardware features to accelerate GPGPU, ML, and AI workloads across mobile, Windows-on-Snapdragon (WoS), and data-center platforms. Work within Qualcomm's GPU research team to propose, evaluate, and drive architectural solutions from concept through collaboration with software and hardware implementation teams.

Experience Level

Mid-level. Typical hire has several years of relevant industry experience (see Education Requirements for degree/experience combinations).

Responsibilities

Key duties include:

  • Design new GPU hardware features and enhance existing GPU architectures for GPGPU, ML, and AI.
  • Develop architectural solutions for mobile, WoS, and data-center GPU platforms.
  • Collaborate with software teams, hardware design teams, standardization bodies, and partners to deliver solutions.
  • Work with hardware simulation/emulation and validation flows to evaluate proposals.
  • Contribute to open-source GPGPU/ML/AI initiatives and influence GPU capabilities for LLMs and large vision models.

Requirements

Must-have technical skills and experience:

  • Strong understanding of GPU architectures, programming models, and application domains.
  • Proficiency with GPU compute APIs (OpenCL, CUDA, Vulkan, or Direct3D 12).
  • Experience with hardware design flows and basic HDL knowledge (Verilog or VHDL).
  • Familiarity with hardware simulation/emulation tools and waveform analysis.
  • Basic knowledge of GPU memory and cache hierarchies.
  • Proficient programming skills in C/C++; Python is a strong plus.

Nice-to-have:

  • Hands-on development, debugging, and optimization of CUDA/OpenCL kernels and GPU compute shaders.
  • Deep understanding of quantization techniques and ML data types for LLMs and large vision models.
  • Experience designing GPU hardware features specifically for ML/AI acceleration.
  • Contributions to or familiarity with open-source ML/GPU projects (for example, llama.cpp, vLLM).

Education Requirements

Bachelor's in Computer Engineering, Computer Science, Electrical Engineering, or related field with 4+ years relevant experience; OR Master's in a related field with 3+ years; OR PhD in a related field with 2+ years. Related work experience in software, hardware, or systems engineering may be accepted in lieu of degree-specific experience as described above.


About the Company

Company: Qualcomm

Headquarters: San Diego, California, United States

Qualcomm is a global leader in semiconductor and telecommunications equipment, specializing in mobile technologies and innovations. Known for its Adreno GPUs, the company provides solutions enabling advancements in mobile gaming, AI, VR/AR, and autonomous driving. Qualcomm's cutting-edge technology and commitment to high-performance, power-efficient designs drive the evolution of mobile graphics and connectivity worldwide.

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Date Posted: 2026-09-03