GPU HW Research Engineer; San Diego/Boxborough
Listed on 2026-06-18
-
Engineering
AI Engineer (Applied/Software), Hardware Engineer, Computer Science, Systems Engineer
Company
Qualcomm Technologies, Inc.
Job AreaEngineering Group, Engineering Group > GPU ASICS Engineering
General SummaryQualcomm’s GPU Research Team is seeking innovative GPU architects to advance state-of-the-art capabilities in Artificial Intelligence (AI),
Machine Learning (ML), and General-Purpose GPU (GPGPU) computing. This is a unique opportunity to design next‑generation GPU architectures that power everything from mobile devices to Windows on Snapdragon (WoS) compute platforms and large‑scale data center GPUs
.
- Collaborate with other GPU architects to design new hardware features and enhance existing GPU architectures for accelerating GPGPU, ML, and AI workloads.
- Develop architectural solutions for diverse platforms, including mobile, WoS, and data center GPUs.
- Work closely with software teams, hardware design teams, standardization bodies, and internal/external partners to deliver cutting‑edge solutions.
- Participate in open‑source GPGPU/ML/AI projects and contribute to industry‑leading initiatives.
- Influence the evolution of GPU capabilities for advanced use cases such as large language models (LLMs) and large vision models (LVMs).
- 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).
- Exposure to hardware simulation/emulation tools and waveform analysis.
- Basic understanding of GPU memory and cache design hierarchy.
- Solid programming skills in C/C++.
- Familiarity with Python is a strong plus.
- Hands‑on experience in development, debugging, and optimization of CUDA and OpenCL kernels, as well as GPU compute shaders.
- Deep understanding of quantization techniques and data types for large language models (LLMs) and large vision models (LVMs).
- Experience designing GPU hardware features for ML/AI acceleration.
- Experience with open‑source projects such as llama.cpp, vLLM, or similar frameworks is a big plus.
- Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, or related field and 4+ years of Software Engineering, Hardware Engineering, Systems Engineering, or related work experience.
- Master's degree in Computer Engineering, Computer Science, Electrical Engineering, or related field and 3+ years of Software Engineering, Hardware Engineering, Systems Engineering, or related work experience.
- PhD in Computer Engineering, Computer Science, Electrical Engineering, or related field and 2+ years of Software Engineering, Hardware Engineering, Systems Engineering, or related work experience.
$ - $
Salary is only one component of total compensation at Qualcomm. A competitive annual discretionary bonus program and opportunity for annual RSU grants are also offered. We provide a highly competitive benefits package to support success at work, at home, and at play.
EEO EmployerQualcomm is an equal opportunity employer; all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or any other protected classification.
#J-18808-Ljbffr(If this job is in fact in your jurisdiction, then you may be using a Proxy or VPN to access this site, and to progress further, you should change your connectivity to another mobile device or PC).