Senior High-Performance LLM Training Engineer - CA, Santa Clara, United States
Originally posted 28 October 2026 by the employer. Relisted by the employer on 29 October 2026.
Optimize LLM training workloads across frameworks like PyTorch and JAX on thousands of GPUs.
About the role
This position focuses on performance analysis and optimization to improve the efficiency of LLM training workloads across frameworks like PyTorch and JAX on thousands of GPUs. You will optimize the deep learning software stack while assisting with hardware roadmaps through processor and system simulator studies.
What you'll do
- Understand, analyze, profile, and optimize AI training workloads across hardware and software platforms. - Implement production-quality software across multiple layers of the deep learning platform stack, from drivers to DL frameworks. - Build and support submissions to the MLPerf Training benchmark suite. - Implement key DL training workloads in proprietary processor and system simulators to enable architecture studies. - Build tools to automate workload analysis, workload optimization, and related workflows.
What you'll need
- PhD in Computer Science, Electrical Engineering, or Computer Engineering with 5+ years of experience, or MS (or equivalent experience) with 8+ years of meaningful work experience. - Strong background in deep learning and neural networks, with a focus on training. - Deep background in computer architecture and familiarity with the fundamentals of GPU architecture. - Proven experience analyzing and tuning application performance, as well as processor and system-level performance modeling. - Programming skills in C++, Python, and CUDA.
Skills: LLM training, performance analysis, GPU architecture, PyTorch, JAX, CUDA
This role has been open 203 days — well above the 87-day median for AI/ML Hardware Engineering roles.
AI/ML Hardware Engineering · AI ML Hardware
|
Open roles in category
506
|
Median days open
87 d
|
Median salary
$236k
|
See the full market breakdown ▾Category comparison, skills in demand, and who else is hiring
| Metric | NVIDIA | All employers we track in this specialty (506 roles · 76 employers) |
|---|---|---|
| Open roles in this specialty | 88 | 506 |
| Open roles in the wider Software, Firmware & Systems family | 1002 | 6363 · 147 employers |
| Median days open | 65 d | 87 d (−22 d vs this employer) |
| Median salary (USD postings) | — | $236k |
Skills observed across this category: LLM training, performance analysis, GPU architecture, PyTorch, JAX, CUDA
Who's hiring in this category
- Qualcomm · 99 open roles · median 120 d
- NVIDIA (this employer) · 89 open roles · median 62 d
- AMD · 32 open roles · median 112 d
- Micron Technology · 27 open roles · median 64 d
- Mobileye · 20 open roles · median 90 d
- Analog Devices · 17 open roles · median 47 d
How we counted: 506 open AI/ML Hardware Engineering (AI ML Hardware) roles from 76 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.