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Head of AI; Frontier ML​/AI Physics

Job in San Francisco, San Francisco County, California, 94199, USA
Listing for: PulseRise Technologies
Full Time position
Listed on 2026-03-16
Job specializations:
  • IT/Tech
    AI Engineer, Machine Learning/ ML Engineer, Data Scientist, Artificial Intelligence
Salary/Wage Range or Industry Benchmark: 125000 - 150000 USD Yearly USD 125000.00 150000.00 YEAR
Job Description & How to Apply Below
Position: Head of AI (Frontier ML / AI for Physics)

Head of AI (Frontier ML / AI for Physics)

Pulse Rise Technologies | Posted Mar 4

Full-time

Negotiable

Master (≥10 yrs)

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.

Details
  • Location:

    Boston or San Francisco (strongly preferred), 3 days/week onsite
  • Work Model:
    Hybrid (relocation support available)
  • Employment Type:

    Full‑time
  • Seniority Level: Executive / Senior Technical Leadership
  • Start Date:

    ASAP
  • Sector: AI for Physics / Scientific Discovery
Key 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, Deep Mind, Meta AI, Google Brain/Deep Mind, 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 Have
  • 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) li>
  • Familiarity with export‑control, dual‑use, or advanced AI safety considerations
Ideal Profile
  • Senior or staff‑level researcher from a frontier AI lab who has shipped major models, agents, or AI‑for‑science systems
  • AI leaders with a strong physics or hard‑science background who transitioned into cutting‑edge ML and now want to return to science‑driven AI challenges
Interview Process
  • Initial screening (motivation, background, mission alignment, security awareness)
  • Cultural and leadership interview with founders and senior technical staff (60 min)
  • Technical deep‑dive interview including custom take‑home (90 min)
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