Senior Manager, AI Power & Performance Engineering - TX, Austin, United States
Originally posted 29 July 2026 by the employer.
About the role
This leader will partner closely with architecture, software, silicon, product management, marketing, and customer-facing teams to ensure AMD solutions achieve competitive leadership in AI workloads spanning Robotics, Physical AI, Automotive, Industrial, and Edge Computing.
What you'll do
- Define and execute AI power and performance strategy across AMD CPU, GPU, NPU, and heterogeneous computing platforms.
- Establish benchmarking methodologies, performance KPIs, competitive analysis frameworks, and workload characterization processes.
- Drive performance optimization across AI models, runtimes, kernels, frameworks, and system software stacks.
- Lead performance readiness for AI solutions across Robotics, Physical AI, Automotive, Industrial, and Edge AI markets.
- Develop customer-ready performance collateral, benchmarking reports, tuning recommendations, and competitive positioning data.
- Build, lead, mentor, and grow a global engineering organization consisting of AI performance, benchmarking, and automation engineers.
What you'll need
- Proven experience in software engineering, system performance, Edge physical AI, embedded platforms, or related domains.
- Proven experience leading engineering teams and delivering complex technical programs.
- Proven experience in Power and Power PnP activities Pre-Silicon and Post-Silicon & Correlation.
- Strong understanding of AI/ML frameworks, inference runtimes, and performance optimization techniques.
- Experience with heterogeneous computing architectures involving CPUs, GPUs, NPUs, and accelerators.
- Bachelor's or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or related field.
Nice to have
- Experience with AMD AI technologies including ROCm, Ryzen AI, ONNX Runtime, MIGraphX, or other AI software stacks.
- Experience in Robotics, Physical AI, Automotive, Industrial, or Edge AI markets.
- Familiarity with generative AI, multimodal AI, computer vision, and robotics workloads.
- Knowledge of AI benchmarking, profiling tools, performance analysis, and power optimization techniques.
- Experience working with geographically distributed engineering organizations.
Skills: AI performance, power efficiency, benchmarking, AI workloads, heterogeneous computing platforms, ROCm
This role has been open 81 days — below the 83-day median for AI/ML Hardware Engineering roles.
AI/ML Hardware Engineering · AI ML Hardware
|
Open roles in category
508
|
Median days open
83 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 (508 roles · 77 employers) |
|---|---|---|
| Open roles in this specialty | 41 | 508 |
| Open roles in the wider Software, Firmware & Systems family | 406 | 6118 · 145 employers |
| Median days open | 81 d | 83 d (−2 d vs this employer) |
| Median salary (USD postings) | — | $236k |
Skills observed across this category: AI performance, power efficiency, benchmarking, AI workloads, heterogeneous computing platforms, ROCm
Who's hiring in this category
- Qualcomm · 99 open roles · median 114 d
- NVIDIA · 93 open roles · median 54 d
- AMD (this employer) · 41 open roles · median 81 d
- Micron Technology · 27 open roles · median 68 d
- Analog Devices · 19 open roles · median 36 d
- Mobileye · 17 open roles · median 80 d
How we counted: 508 open AI/ML Hardware Engineering (AI ML Hardware) roles from 77 employers tracked in the SemiconductorJobs index, counted 18 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.