Distributed Systems Software Engineer, Collectives - CA, San Jose, United States
Originally posted 28 October 2026 by the employer.
About the role
As a member of the Collectives and Network Performance team, you will contribute to developing, testing, and optimizing collective communication and networking software for AMD GPUs. You will help improve training and inference performance across multi-GPU and multi-node systems in collaboration with internal GPU library, runtime, and ROCm teams.
What you'll do
- Implement, test, and debug features in collective communication libraries and network software. - Profile LLM, diffusion, multimodal, RecSys, and generative AI workloads on single-node and multi-node systems to identify performance bottlenecks. - Run performance experiments across AMD GPU generations and network configurations, summarizing results for the team. - Contribute to tools and infrastructure for performance measurement, regression tracking, and reporting. - Support new model enablement and out-of-the-box performance efforts across AI frameworks while collaborating with internal teams and open-source communities. - Apply engineering practices, including code reviews, testing, and documentation, to deliver maintainable code.
What you'll need
- Bachelor’s or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent. - Proficiency in C++ development with a solid foundation in Linux environments. - Foundational understanding of computer architecture and networking concepts. - Experience with profiling and debugging performance issues.
Nice to have
- Understanding of collective communication concepts (such as all-reduce, all-to-all) and familiarity with libraries such as RCCL, NCCL, or MPI, as well as networking fundamentals such as RDMA, NICs, and interconnects. - Foundational knowledge of GPU architecture and experience with HIP, CUDA, or similar GPU programming. - Familiarity with AI frameworks such as PyTorch, JAX, vLLM, or SGLang, and distributed training or inference concepts. - Proficiency in Python with experience in debugging, profiling, and writing tests. - Professional experience in software development with exposure to performance engineering, systems software, networking, or GPU programming.
Skills: RCCL, NCCL, C++, collective communication, ROCm, RDMA
This role has been open 0 days — well below the 55-day median for Infrastructure/Platform Software roles.
Infrastructure/Platform Software · GPU Software Stack
|
Open roles in category
258
|
Median days open
55 d
|
Median salary
$220k
|
See the full market breakdown ▾Category comparison, skills in demand, and who else is hiring
| Metric | AMD | All employers we track in this specialty (258 roles · 19 employers) |
|---|---|---|
| Open roles in this specialty | 55 | 258 |
| Open roles in the wider Software, Firmware & Systems family | 389 | 6395 · 147 employers |
| Median days open | 57 d | 55 d (+2 d vs this employer) |
| Median salary (USD postings) | — | $220k |
Skills observed across this category: RCCL, NCCL, C++, collective communication, ROCm, RDMA
Who's hiring in this category
- NVIDIA · 127 open roles · median 58 d
- AMD (this employer) · 55 open roles · median 57 d
- Intel Corporation · 29 open roles · median 15 d
- Qualcomm · 17 open roles · median 188 d
- Arm Holdings · 8 open roles · median 1 d
- Graphcore · 4 open roles · median 8 d
How we counted: 258 open Infrastructure/Platform Software (GPU Software Stack) roles from 19 employers tracked in the SemiconductorJobs index, counted 29 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.