Open Source Software Engineer — ML Systems & AMD Hardware - Remote
Originally posted 19 October 2026 by the employer.
About the role
As an Open Source Software Engineer, you will build and optimize machine learning systems that integrate with AMD hardware. You will design, implement, test, and ship open source integrations with widely used AI systems and frameworks across GPU systems and high-performance computing.
What you'll do
- Develop and maintain open source integrations between ML/AI software and AMD hardware. - Optimize kernels and critical execution paths for AMD GPUs, including kernel fusions and GPU execution pipelines. - Profile workloads, identify performance bottlenecks across compute, memory bandwidth, synchronization, and data movement, and implement measurable optimizations. - Work with LLM inference systems to evaluate how model architecture, data layout, quantization, and execution strategy impact performance. - Contribute high-quality code upstream to open source projects, participate in code reviews, and collaborate with maintainers. - Write unit, integration, and performance tests, while maintaining automated testing, CI, and validation infrastructure.
What you'll need
- Strong familiarity with LLM systems, inference workloads, compute, and optimization. - Experience optimizing GPU kernels, particularly for AMD architectures. - Understanding of kernel fusion, GPU execution, and pipelined execution. - Understanding of performance tradeoffs across compute, memory bandwidth, synchronization, and data movement. - Familiarity with open source development practices, including code review, automated testing, CI, and upstream contribution. - Knowledge of graphics processor pipelines or experience with quantized data layouts and model quantization techniques.
Nice to have
- Experience with one or more of vLLM, SGLang, llama.cpp, ROCm, CUDA, or Vulkan / SPIR-V. - Experience in AMD GPU architecture, performance analysis, and LLM inference and serving systems. - Experience with multiple GPU programming languages, kernel DSLs, performance profiling, and benchmarking. - Track record of contributing to large, active open source projects, including open source CI and release processes. - Bachelor's or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field (or equivalent professional experience).
Skills: open source software, machine learning systems, AMD hardware, GPU kernel optimization, LLM inference, ROCm
This role has been open 0 days — well below the 59-day median for Infrastructure/Platform Software roles.
Infrastructure/Platform Software · GPU Software Stack
|
Open roles in category
229
|
Median days open
59 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 (229 roles · 19 employers) |
|---|---|---|
| Open roles in this specialty | 50 | 229 |
| Open roles in the wider Software, Firmware & Systems family | 408 | 6166 · 145 employers |
| Median days open | 61 d | 59 d (+2 d vs this employer) |
| Median salary (USD postings) | — | $236k |
Skills observed across this category: open source software, machine learning systems, AMD hardware, GPU kernel optimization, LLM inference, ROCm
Who's hiring in this category
- NVIDIA · 113 open roles · median 56 d
- AMD (this employer) · 50 open roles · median 61 d
- Intel Corporation · 24 open roles · median 10 d
- Qualcomm · 18 open roles · median 123 d
- Arm Holdings · 5 open roles · median 116 d
- d-Matrix · 2 open roles · median 124 d
How we counted: 229 open Infrastructure/Platform Software (GPU Software Stack) roles from 19 employers tracked in the SemiconductorJobs index, counted 19 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.