Director, Applied AI Research - Compute & Hardware

WHAT YOU DO AT AMD CHANGES EVERYTHING   At AMD, our mission is to build great products that accelerate next-generation computing experiences—from AI and data centers, to PCs, gaming and embedded systems. Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuity and a shared passion to create something extraordinary. When you join AMD, you’ll discover the real differentiator is our culture. We push the limits of innovation to solve the world’s most important challenges—striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives. Join us as we shape the future of AI and beyond.   Together, we advance your career.

AMD is looking for a Director of Applied AI Research to lead research that sits where AI, compute, and AMD's hardware meet. You will lead applied research that uses AI to advance AMD's compute and hardware, with agents, reinforcement learning, and recursive self-improvement (RSI) as central tools for making those gains compound. You will collaborate with our AI research teams and hardware engineering teams to make this happen.   THE PERSON: You will build and lead a team of applied researchers and research engineers, set technical direction across compute- and hardware-focused workstreams, and own the path from promising idea to validated, adopted capability. The ideal candidate is a researcher who is energized by real systems and real constraints. It’s someone who can frame a research question, run the experiment, build the verifier that proves it worked, and partner with different engineering teams to land it. 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 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   PREFERRED EXPERIENCE: 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