Director, AI Research - Recursive Self-Improvement

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AMD is looking for a Director of AI Research to lead AMD's recursive self-improvement (RSI) agenda: using AI—and reinforcement learning in particular—to make AMD's hardware design, kernel and compiler optimization, and engineering workflows measurably better, then feeding those gains back into the loop.

This is a deeply technical leadership role aimed squarely inside AMD. You will build and lead a research team, set the technical direction for the RSI flywheel, and partner across silicon, software, compiler, and engineering-productivity teams to turn research into compounding internal advantage. The ideal candidate is a recognized AI researcher who can go deep on RL training and systems and has strong opinions about what makes self-improving loops actually work (and where they break).

We are open to candidates who want to remain hands‑on as player‑coaches as well as those who lead primarily through their teams.

• Define and own AMD's internal recursive self-improvement research agenda—where AI improves AMD's hardware, kernels, compilers, and engineering workflows, and how those gains compound over time

• Build, lead, and mentor a high-caliber team of AI researchers and research engineers; set research direction, hiring bar, and standards for technical rigor

• Drive RL-based research on concrete internal targets—kernel and PPA optimization, design‑space exploration, and code/workflow generation—grounded in measurable, verifiable improvement

• Design and own the verification and evaluation infrastructure (fast simulators, "slice" verifiers, benchmarks) needed to run self‑improvement loops safely and trust their results

• Confront the hard failure modes of self‑improving systems directly—reward hacking, evaluation gaming, and reward‑signal scaling—and build research programs to detect and mitigate them

• Partner deeply with silicon, architecture, compiler, and engineering‑productivity teams to embed research into real AMD design and development flows

• Set and track measurable goals for the program—verified performance gains, cycle‑time reduction, and the rate at which improvements feed back into the loop

• Drive AMD's broader move toward AI‑native engineering, helping rearchitect how internal teams build hardware and software around AI in the loop

• Represent the RSI research agenda to executive leadership; communicate progress, risks, and roadmap implications to both technical and business audiences

• Stay at the frontier of RL and AI‑for‑systems research and translate emerging techniques into internal opportunity

• Demonstrated technical leadership in AI/ML research, with a track record of impactful published work and/or research shipped into production systems

• Deep, current expertise in reinforcement learning, including reward modeling, training pipelines, and the practical failure modes of RL at scale

• Hands‑on understanding of AI‑for‑systems problems—code generation, compiler/kernel optimization, design‑space exploration, or hardware/software co‑design

• Experience building coding RL loops

• Experience leading research teams and setting technical direction across multiple concurrent programs

• 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 embedding research into engineering organizations

• Track record of attracting, hiring, and…