2027 PhD AI Model Optimization & Software Engineer Intern/Co-op - CA, San Jose, United States
Originally posted 16 September 2026 by the employer.
About the role
This role involves developing and optimizing AI software for various platforms, focusing on AI model optimization, framework engineering, and performance analysis.
What you'll do
- Develop, benchmark, and optimize AI software for training, fine-tuning, and inference across CPU, GPU, and accelerator platforms.
- Profile AI workloads, identify hardware and software bottlenecks, and implement performance improvements.
- Design, prototype, and optimize GPU or CPU kernels using technologies such as HIP, CUDA, OpenCL, or Triton.
- Research and implement AI model optimization methods such as quantization, low-precision inference, sparsity, pruning, or distillation.
- Contribute to AI frameworks, libraries, execution runtimes, and deployment technologies like PyTorch, TensorFlow, JAX, ONNX Runtime, vLLM, or SGLang.
- Develop or evaluate parallel and distributed computing methods, including collective communication operations and scalable training or inference techniques.
What you'll need
- Currently enrolled in a U.S.-based PhD program in Computer Science, Computer Engineering, Artificial Intelligence, Machine Learning, Electrical Engineering, or a related technical field.
- Programming experience in Python and/or C/C++.
- Experience with one or more AI frameworks or runtimes, such as PyTorch, TensorFlow, JAX, ONNX Runtime, vLLM, or SGLang.
- Experience, coursework, research, or project work in AI model inference, training, fine-tuning, or performance optimization.
- Experience, coursework, research, or project work in GPU or accelerator kernel development.
- Familiarity with software development tools such as Git, CMake, Make, Conda, or Docker.
Nice to have
- Research publications, preprints, open-source contributions, or participation in the AI and machine learning developer community.
Skills: AI model optimization, GPU computing, AI software infrastructure, PyTorch, TensorFlow, CUDA
This role has been open 27 days — well below the 56-day median for Infrastructure/Platform Software roles.
Infrastructure/Platform Software · GPU Software Stack
|
Open roles in category
231
|
Median days open
56 d
|
Median salary
$236k
|
See the full market breakdown ▾Category comparison, skills in demand, and who else is hiring
| Metric | AMD | All employers we track in this specialty (231 roles · 20 employers) |
|---|---|---|
| Open roles in this specialty | 52 | 231 |
| Open roles in the wider Software, Firmware & Systems family | 405 | 6119 · 146 employers |
| Median days open | 64 d | 56 d (+8 d vs this employer) |
| Median salary (USD postings) | — | $236k |
Skills observed across this category: AI model optimization, GPU computing, AI software infrastructure, PyTorch, TensorFlow, CUDA
Who's hiring in this category
- NVIDIA · 119 open roles · median 54 d
- AMD (this employer) · 52 open roles · median 64 d
- Qualcomm · 19 open roles · median 105 d
- Intel Corporation · 16 open roles · median 6 d
- Arm Holdings · 5 open roles · median 111 d
- d-Matrix · 2 open roles · median 119 d
How we counted: 231 open Infrastructure/Platform Software (GPU Software Stack) roles from 20 employers tracked in the SemiconductorJobs index, counted 14 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.