Senior Manager, AI Power & Performance Engineering

AMD AMD · Semiconductors · Austin, TX · Engineering

Senior Manager, AI Power & Performance Engineering at AMD, leading a team to deliver industry-leading AI performance, power efficiency, benchmarking, characterization, and optimization across AMD's Embedded and Edge AI platforms. The role focuses on ensuring competitive leadership in AI workloads for Robotics, Physical AI, Automotive, Industrial, and Edge Computing, involving optimization across AI models, runtimes, kernels, frameworks, and system software stacks, and influencing hardware/software roadmaps. It requires strong leadership in building and managing global engineering teams, defining AI power and performance strategy, establishing benchmarking methodologies, and driving automation for performance validation.

What you'd actually do

  1. Define and execute AI power and performance strategy across AMD CPU, GPU, NPU, and heterogeneous computing platforms.
  2. Establish benchmarking methodologies, performance KPIs, competitive analysis frameworks, and workload characterization processes.
  3. Drive performance optimization across AI models, runtimes, kernels, frameworks, and system software stacks.
  4. Build, lead, mentor, and grow a high-performing global engineering organization consisting of AI performance, benchmarking, and automation engineers.
  5. Drive development of scalable benchmarking, automation, telemetry, profiling, and analytics infrastructure.

Skills

Required

  • software engineering
  • system performance
  • Edge physical AI
  • embedded platforms
  • leading engineering teams
  • delivering complex technical programs
  • Power and Power PnP activities Pre-Silicon and Post-Silicon & Correlation
  • AI/ML frameworks
  • inference runtimes
  • performance optimization techniques
  • heterogeneous computing architectures
  • CPUs
  • GPUs
  • NPUs
  • accelerators
  • communication skills
  • organizational skills
  • leadership skills

Nice to have

  • AMD AI technologies including ROCm, Ryzen AI, ONNX Runtime, MIGraphX, or other AI software stacks
  • Robotics
  • Physical AI
  • Automotive
  • Industrial
  • Edge AI markets
  • generative AI
  • multimodal AI
  • computer vision
  • robotics workloads
  • AI benchmarking
  • profiling tools
  • performance analysis
  • power optimization techniques
  • working with geographically distributed engineering organizations

What the JD emphasized

  • 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.

Other signals

  • delivering industry-leading AI performance
  • power efficiency, benchmarking, characterization, and optimization
  • AMD's Embedded and Edge AI platforms
  • competitive leadership in AI workloads spanning Robotics, Physical AI, Automotive, Industrial, and Edge Computing
  • performance-per-watt leadership
  • AI workload enablement and optimization
  • customer-ready performance collateral
  • performance scalability, efficiency, reliability, and production readiness
  • AI/ML frameworks, inference runtimes, and performance optimization techniques
  • heterogeneous computing architectures involving CPUs, GPUs, NPUs, and accelerators