Head of AI (Frontier ML / AI for Physics)

Remote Full-time
About the position

We are looking for an exceptional Head of AI to lead and define the AI research agenda of a well-funded, frontier AI-for-physics company. This is a hands-on technical leadership role for someone who has operated at the highest levels of modern machine learning and is ready to build and scale an AI organization from the ground up. The role combines foundation model research, reinforcement learning, and agentic systems applied to scientific discovery in physics. You will work at the intersection of large-scale simulation, hypothesis generation, and validation, shaping systems capable of discovering new physical insights. This position requires deep ML expertise, strong scientific grounding, and proven leadership in demanding research environments. It offers significant ownership, equity participation, and the opportunity to define a long-term AI vision in a mission-driven company.

Responsibilities
• Define and drive the AI research roadmap across foundation models, reinforcement learning, and agentic systems
• Architect and directly contribute to model design, large-scale training schemes, and advanced agent behaviors
• Design training infrastructure and evaluation frameworks for physics-focused AI systems
• Recruit, hire, mentor, and manage a high-performance AI research and engineering team
• Establish high standards for experimentation, code review, project prioritization, and cross-functional collaboration
• Serve as the internal AI thought leader, guiding architectural decisions and long-term technical direction
• Collaborate closely with physicists to design benchmarks, validation harnesses, and scientifically rigorous evaluation methods
• Align AI strategy with company milestones, scientific objectives, and security constraints
• Selectively represent the company’s AI vision to advisors, investors, and strategic stakeholders

Requirements
• Experience at a top frontier or “Neolab”-style AI lab (e.g., OpenAI, Anthropic, DeepMind, Meta AI, Google Brain/DeepMind, xAI, etc.), with leadership or co-leadership of major AI initiatives
• Deep expertise in foundation model pretraining, reinforcement learning (PPO, SAC, self-play), and large-scale optimization
• Strong experience with distributed training systems (multi-GPU / multi-node, CUDA, NCCL)
• Demonstrated experience building and managing high-performing research or engineering teams
• Ability to define ambitious research goals and translate them into structured, executable projects
• Strong background in physics, mathematics, or other hard sciences
• Experience collaborating across AI and scientific domains
• High professional maturity and comfort operating in demanding, frontier research environments

Nice-to-haves
• Experience with scientific ML (physics-informed neural networks, neural PDE solvers, differentiable simulations, surrogate modeling)
• Prior work integrating AI models with large-scale simulations (science, robotics, gaming, or similar domains)
• Familiarity with export-control, dual-use, or advanced AI safety considerations

Benefits
• equity participation

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