Head of Core AI

Physical Superintelligence is a startup with roots at Google, NVIDIA, Harvard, Meta, MIT, Oxford, Johns Hopkins, Cambridge, and the Perimeter Institute building AI systems to discover new physics at scale.

Our mission is to discover and commercialize transformative physics breakthroughs at scale with artificial superintelligence, safely, verifiably, and for broad public benefit.

The last century's golden age of physics gave us transistors, lasers, and nuclear energy. We believe artificial superintelligence will unlock the next one. We're creating the infrastructure to industrialize scientific discovery and usher in this new era.

We have one product: new physics, at scale.

We are seeking a Head of Core AI to lead Core AI: the team that builds the models, agents, and training systems that do physics. This is applied work in service of a product. Everything Core AI builds exists to make PSI's AI-for-physics capability better.

• Core AI is the organization responsible for the AI models, agentic harnesses, and inference/training algorithms: the AI research that the Applied AI and Physics organizations leverage.

• Set the Core AI roadmap and own the resulting AI research portfolio in service of one goal: making PSI's AI systems better at doing real physics. Own the people and the delivery, set direction, kill weak lines of work, and double down on what works.

• Hold the work to one bar: does it produce physics a real physicist would trust. You own the training and evaluation infrastructure the rest of the company depends on to run Core AI at scale, and you are accountable for closing the gap between a result that looks good and one that is real.

• Stay technical. This is a player-coach role: you carry individual technical work, review work and code, and set the bar in person.

• Continuously review related work and emerging discussions in AI to stay informed about advancements in the field and to evaluate the most promising new ideas.

• Partner with Applied AI, which turns Core AI's work into products and customer engagements, and with Engineering, which owns the platform infrastructure your systems train, evaluate, and run on. Core AI is only as valuable as what these teams can build on top of it.

• Hire and develop world-class talent, keeping the bar high while Core AI grows.

• A track record of leading AI research teams that shipped: you have run an industrial AI research group at a frontier lab, a fast-moving AI company, or equivalent, and the work made it into production systems or into results the field recognizes.

• At least three years of direct people management: hiring, performance reviews, and career development for the people who reported to you.

• Deep technical fluency in modern ML: reinforcement learning, agentic systems, large-scale training, and evaluation methodology. You have personally built and trained systems that beat non-trivial baselines, and you can still do so.

• Publications and standing at top ML venues (NeurIPS, ICML, ICLR, or comparable), or an AI research artifact the community has adopted, as evidence of the caliber of your work.

• AI research judgment under commercial constraints. You know when a research direction is dead, when a benchmark is being gamed, and when to trade elegance for something that ships this quarter.

• Enough physics or mathematics background to hold a substantive conversation with domain scientists and to understand whether the science is real.

• Hands-on experience applying agents or RL to science, mathematics, code, or other complex-reasoning domains.

• Experience scaling an AI research organization through rapid company growth, including hiring, leveling, and performance management.

• Experience with AI-for-science specifically: simulators, verification, scientific tool use.

We hold a high technical bar and give people full ownership of their work, from spec to ship to on-call. We write contracts before logic, test against real systems instead of mocks, and favor simple designs that ship over clever ones that do not. Our development process is AI-native: we work with agentic coding tools daily, write specs that are legible to humans and agents alike, and lead with leverage.

This is an in-person role based in Boston. We offer competitive compensation including salary, benefits, and meaningful early-stage equity. We evaluate on AI research judgment, technical depth, leadership track record, and shipping velocity. We are an equal opportunity employer and value diverse perspectives in building platforms for AI-driven discovery.