GPU Kernel Development Engineer (Multiple Levels Available)
$116,900 - $175,300 USD yearly
Originally posted 18 December 2025 by the employer.
Develop high-performance kernels and runtimes for Adreno GPUs across Android, Linux, and Windows.
About the role
The Qualcomm GPU Software team is developing high performance kernels and runtimes for accelerating GPGPU operations such as Machine Learning and Image Processing. This role involves developing and optimizing Adreno GPU drivers for standard APIs across Android, Linux, and Windows.
What you'll do
- Develop and optimize Adreno GPU drivers for standard APIs such as OpenCL, OpenGL ES, Vulkan, and DirectX. - Build runtimes and frameworks that support Machine Learning and other GPGPU operations. - Write code for features, drivers, and APIs using languages including C, C++, and Python. - Collaborate with hardware designers to understand, improve, and document hardware/software interfaces. - Develop unit tests, samples, and design documentation while supporting external developers and OEMs.
What you'll need
- Bachelor's degree in Applied Mathematics, Computer Science, Computer Engineering, Electrical Engineering, Software Engineering, or related field with 2+ years of relevant engineering experience (or Master's with 1+ year, or PhD). - 1+ year of academic or work experience with programming languages suitable for graphics, including C++ or C. - Familiarity with a GPGPU API such as CUDA or OpenCL. - Understanding of data structures, algorithms, and object-oriented programming.
Nice to have
- Knowledge of Machine Learning Theory. - Familiarity with a Deep Learning Framework such as PyTorch. - Knowledge of GPGPU application development including Mathematical Operations and Image Processing. - Experience with device driver development, including GPU or CPU. - Programming experience with Graphics APIs such as OpenGL ES, Vulkan, DX11, or DX12. - Exposure to embedded systems, real-time operating systems, and ARM architecture. - Familiarity with Git or other SCM tools.
Skills: GPU, Machine Learning, inference, training, C++, CUDA
This role has been open 200 days — well above the 54-day median for Infrastructure/Platform Software roles.
Infrastructure/Platform Software · GPU Software Stack
|
Open roles in category
244
|
Median days open
54 d
|
Median salary
$221k
|
See the full market breakdown ▾Category comparison, skills in demand, and who else is hiring
| Metric | Qualcomm | All employers we track in this specialty (244 roles · 20 employers) |
|---|---|---|
| Open roles in this specialty | 18 | 244 |
| Open roles in the wider Software, Firmware & Systems family | 735 | 6250 · 144 employers |
| Median days open | 130 d | 54 d (+76 d vs this employer) |
| Median salary (USD postings) | — | $221k |
Skills observed across this category: GPU, Machine Learning, inference, training, C++, CUDA
Who's hiring in this category
- NVIDIA · 122 open roles · median 58 d
- AMD · 51 open roles · median 54 d
- Intel Corporation · 26 open roles · median 14 d
- Qualcomm (this employer) · 18 open roles · median 129 d
- Arm Holdings · 5 open roles · median 122 d
- Graphcore · 4 open roles · median 4 d
How we counted: 244 open Infrastructure/Platform Software (GPU Software Stack) roles from 20 employers tracked in the SemiconductorJobs index, counted 25 Oct 2026. Specialty figures count only roles carrying this exact specialty label, so an employer's related work in neighbouring specialties is not included there — it is counted in the wider Software, Firmware & Systems family row. Figures refresh nightly.
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