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Director, Applied AI Research - Compute & Hardware

AMD· Engineering
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Hybrid (Santa Clara, CA)$246.4k - $369.6kFull-timePosted 3mo ago

About the role

Director of Applied AI Research to lead research at the intersection of AI, compute, and AMD hardware, focusing on agents, reinforcement learning, and recursive self-improvement to drive measurable gains on compute and hardware targets.

Responsibilities

  • Define and own an applied AI research agenda focused on compute and hardware—kernel and compiler optimization, PPA and design-space exploration, and AI-for-systems, on the highest priority engineering projects at the company
  • Build, lead, and mentor a high-caliber team of applied researchers and research engineers; set research direction, hiring bar, and standards for rigor and delivery
  • Use recursive self-improvement loops to drive compounding, verifiable gains on concrete compute and hardware targets
  • Design and partner with teams to own the evaluation, simulation, and verification infrastructure (fast verifiers, benchmarks) that makes applied results trustworthy and ready to adopt
  • Confront the practical failure modes of RL and self-improving loops—reward hacking, evaluation gaming, reward-signal scaling—and build research and/or partner with research teams to detect and mitigate them
  • Own the full path from research to impact: frame the problem, run the experiments, validate the result, and partner with engineering to land it in real flows
  • Partner deeply across silicon, architecture, compiler, software, and AI-for-hardware engineering teams to ground research in real problems and ensure adoption
  • Set and track measurable outcomes—verified performance and PPA gains, cycle-time reduction, and the rate at which improvements feed back into the loop
  • Represent the applied research agenda to executive leadership; communicate progress, trade-offs, and roadmap implications to technical and business audiences
  • Stay at the frontier of RL and AI-for-systems research and translate emerging techniques into applied opportunity for AMD

Qualifications

  • Demonstrated technical leadership in applied AI/ML research, with a track record of research that reached real systems or production impact
  • Deep, current expertise in reinforcement learning, including reward modeling, training pipelines, and the practical failure modes of RL at scale
  • Strong grounding in AI-for-systems and compute/hardware problems—kernel or compiler optimization, design-space exploration, or hardware/software co-design
  • Experience building the evaluation, simulation, or verification infrastructure that applied research and training loops depend on
  • Experience leading research teams and setting direction across multiple concurrent workstreams
  • Ability to remain hands-on with training pipelines, kernels, or research prototyping while leading a team
  • Strong cross-functional collaboration skills, with a track record of landing research inside engineering organizations
  • Track record of attracting, hiring, and developing top applied AI research talent
  • PhD in Computer Science, Electrical Engineering, Machine Learning, or a related field, or equivalent research experience and demonstrated impact

Skills

Required:Applied AI/ML research leadershipReinforcement learningAI-for-systemsEvaluation/infrastructure for applied researchPeople leadership
Nice to have:Hands-on with research prototyping

Benefits

  • Benefits offered are described: AMD benefits at a glance.
Last updated Oct 22, 2026. Interested? Apply on the company site.
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