Director, Applied AI Research - Compute & Hardware

Job Title

Director, Applied AI Research - Compute & Hardware

Role Summary

Lead applied AI research at the intersection of AI, compute, and hardware to deliver validated, adoptable capabilities that improve performance, power, area (PPA), and engineering cycle time.

Build and manage a team of applied researchers and research engineers; partner across silicon, architecture, compiler, software, and AI engineering teams to move research into production flows.

Experience Level

Senior-level (Director). The role requires proven technical leadership in applied AI/ML research and a track record of research delivered into real systems or production.

Responsibilities

The role owns an applied research agenda and the path from idea to deployed capability. Key responsibilities include:

• Define and own applied AI research priorities focused on compute and hardware (kernel/compiler optimization, PPA and design-space exploration, AI-for-systems).
• Build, lead, and mentor a high-caliber team of applied researchers and research engineers; set technical direction and hiring standards.
• Develop and apply recursive self-improvement loops to produce compounding, verifiable gains on compute and hardware targets.
• Design, partner on, and own evaluation, simulation, and verification infrastructure (fast verifiers, benchmarks) to make results trustworthy and adoptable.
• Identify and mitigate practical RL failure modes (reward hacking, evaluation gaming, reward-signal scaling) through research or partnerships.
• Own the end-to-end path from problem framing to experiment, validation, and adoption by engineering teams.
• Set and track measurable outcomes: verified performance/PPA gains, cycle-time reduction, and feedback rate into improvement loops.
• Communicate progress and trade-offs to executive and technical audiences; represent applied research roadmap to leadership.

Requirements

Core technical and leadership requirements. Education credentials are summarized separately below.

Must-have:

• Technical leadership in applied AI/ML research with impact on real systems or production.
• Deep, current expertise in reinforcement learning, including reward modeling, training pipelines, and scaling failure modes.
• Strong grounding in AI-for-systems and compute/hardware problems (kernel/compiler optimization, design-space exploration, hardware/software co-design).
• Experience building evaluation, simulation, or verification infrastructure for applied research and training loops.
• Experience leading research teams and directing multiple concurrent workstreams; ability to remain hands-on when required.
• Proven cross-functional collaboration skills and a track record of landing research inside engineering organizations.
• Experience attracting, hiring, and developing top applied AI research talent.

Nice-to-have:

• Prior work on compiler/kernel internals, PPA optimization at chip/RTL/system level, or production ML systems for systems-level problems.
• Experience with large-scale RL training infrastructure and automated evaluation at scale.

Education Requirements

PhD in Computer Science, Electrical Engineering, Machine Learning, or a related field, or equivalent research experience with demonstrated impact.

About the Company

Company: Advanced Micro Devices

Headquarters: Sunnyvale, California, USA

Advanced Micro Devices, or AMD, is a global semiconductor company that designs and manufactures microprocessors, graphics processors, and related technologies for a variety of computing devices. Known for pushing the boundaries of innovation, AMD's mission is to deliver high-performance computing solutions for AI, data centers, gaming, and embedded applications. They foster a collaborative, inclusive culture focused on creativity and problem-solving, aiming to drive progress and excellence in technology.