Senior AI Systems Performance Engineer - TX, Austin, United States
Originally posted 6 October 2026 by the employer.
About the role
What you'll do
- Lead AI workload benchmarking and performance characterization efforts across AMD AI-enabled embedded and client platforms.
- Design and maintain scalable benchmarking infrastructure, automated performance dashboards, and workload analysis methodologies.
- Drive deep root-cause analysis of performance bottlenecks across software, firmware, operating system, silicon, memory, and platform layers.
- Utilize advanced profiling and tracing tools to characterize AI workload behavior and identify optimization opportunities.
- Analyze power, performance, throughput, latency, and efficiency tradeoffs across diverse AI deployments.
- Mentor junior engineers and help establish best practices across the AI performance engineering organization.
What you'll need
- Deep understanding of AI inference workloads and performance optimization techniques.
- Strong hands-on experience with AI frameworks such as PyTorch, ONNX Runtime, vLLM, TensorFlow, ROCm, Ryzen AI, or similar technologies.
- Experience analyzing and optimizing performance of LLMs, VLMs, multimodal workloads, computer vision applications, and generative AI systems.
- Advanced knowledge of Linux systems, performance analysis, and debugging methodologies.
- Strong understanding of AMD APUs, GPUs, CPUs, NPUs, unified memory architectures, or similar heterogeneous computing platforms.
- Experience utilizing low-level profiling, tracing, power analysis, and performance characterization tools.
- Extensive experience with BIOS configuration, platform tuning, and system optimization techniques.
- Strong scripting and automation skills using Python, Shell, or similar technologies.
Nice to have
- Demonstrated ability to communicate complex technical findings to executives, customers, product teams, and senior engineering leadership.
- Experience supporting customer-facing performance discussions, technical reviews, or competitive benchmarking initiatives.
Skills: AI workload performance, benchmarking, performance bottlenecks, hardware and software, PyTorch, ROCm
This role has been open 3 days — well below the 76-day median for AI/ML Hardware Engineering roles.
AI/ML Hardware Engineering · AI ML Hardware
|
Open roles in category
520
|
Median days open
76 d
|
Median salary
$235k
|
See the full market breakdown ▾Category comparison, skills in demand, and who else is hiring
| Metric | AMD | All employers we track in this specialty (520 roles · 76 employers) |
|---|---|---|
| Open roles in this specialty | 40 | 520 |
| Open roles in the wider Software, Firmware & Systems family | 404 | 6047 · 146 employers |
| Median days open | 69 d | 76 d (−7 d vs this employer) |
| Median salary (USD postings) | — | $235k |
Skills observed across this category: AI workload performance, benchmarking, performance bottlenecks, hardware and software, PyTorch, ROCm
Who's hiring in this category
- Qualcomm · 100 open roles · median 113 d
- NVIDIA · 92 open roles · median 57 d
- AMD (this employer) · 40 open roles · median 69 d
- Micron Technology · 31 open roles · median 63 d
- Mobileye · 19 open roles · median 71 d
- Analog Devices · 17 open roles · median 27 d
How we counted: 520 open AI/ML Hardware Engineering (AI ML Hardware) roles from 76 employers tracked in the SemiconductorJobs index, counted 9 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.