Director, Applied AI Research, Compute & Hardware

What you'll do

• Define and own an applied AI research agenda focused on compute and hardware optimization.
• Build, lead, and mentor a high-caliber team of applied researchers and research engineers.
• Use recursive self-improvement loops to drive verifiable gains on concrete compute and hardware targets.
• Design and manage the evaluation, simulation, and verification infrastructure for trusted results.
• Mitigate practical failure modes of reinforcement learning such as reward hacking and evaluation gaming.
• Manage the full lifecycle from framing research problems to landing validated results in production flows.
• Partner with silicon, architecture, compiler, and software teams to ground research in real engineering problems.
• Communicate progress, trade-offs, and roadmap implications to executive leadership and technical audiences.

What we're looking for

• PhD in Computer Science, Electrical Engineering, Machine Learning, or a related field, or equivalent research experience and demonstrated impact.
• Demonstrated technical leadership in applied AI/ML research with a track record of production impact.
• Deep expertise in reinforcement learning, including reward modeling, training pipelines, and managing failure modes at scale.
• Strong grounding in AI-for-systems and hardware problems like kernel optimization and design-space exploration.
• Experience building evaluation, simulation, or verification infrastructure for research and training loops.
• Proven ability to lead, mentor, and hire high-caliber teams of researchers and engineers.
• Ability to remain hands-on with training pipelines, kernels, or research prototyping while leading a team.
• Strong cross-functional collaboration skills to land research within engineering organizations.