Head of Applied AI

Overview 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 Applied AI to lead the organization that puts PSI's AI and physics capability to work on real engineering systems. Applied AI at PSI is applied physics plus AI: thermal and fluid systems, electrical power distribution, structures, and the coupled models that tie them together, built for customers who need answers their current tools cannot give them. Role and Responsibilities Applied AI is the organization responsible for solving customers' engineering problems with our models, simulations, and agents: thermal, fluid, electrical, structural, and the coupling between them. This is applied science aimed at revenue. Build the organization. Grow the team of applied physicists and engineers, define how it works, and own its results. Hire for strengths, not for the absence of weaknesses: people strong across most of the domains and deep in one, who start on open-ended problems without being told how and pick up an unfamiliar domain when the work needs it. Set the technical direction. Decide where a classical solver is required, where a learned model is enough, how the two are validated against measured data, and when a result is good enough to put in front of a customer. Own customer delivery end-to-end. Scope each engagement around the customer's actual problem, build the models and simulations that solve it, and ship something that runs in their environment. Every engagement leaves behind a reusable technical capability. Own the interfaces through which researchers and customers put PSI's AI and physics work to use. These exist to make the underlying science usable and trustworthy. Partner with go-to-market on scoping and expansion: be the technical counterpart to sales, decide what we can credibly promise, and serve as the escalation point when an engagement is at risk. Stay technical. This is a player-coach role: carry individual technical work on engagements, and set the bar for what shipped means by shipping working science. Pull research from Core AI and domain expertise from Physics into what you ship, and build on the infrastructure Engineering runs. You are the team that turns the rest of the company's work into something a customer pays for, so these partnerships are constant. What We're Looking For A PhD, or an equivalent research record, in mechanical, electrical, aerospace, or chemical engineering, applied physics, or computational science. You have modeled a physical system that mattered and validated the model against ground truth, and you can say how you knew it was right and what you did when it was not. Eight or more years applying ML and simulation to engineering problems governed by physical constraints, thermal, fluid, electrical, or structural, with at least three leading a technical team that delivered to customers or partners at a company known for technical rigor. Recommenders, ads, and business analytics do not count toward this. At least three years of direct people management: hiring, performance reviews, and career development for the people who reported to you. A track record of building a function: you have hired and led a customer-facing technical team from small or from scratch, and the function outlived your direct involvement in every deal. Depth in at least one engineering domain: thermal and fluid, power systems, structural, or electrochemistry. You can build a model, debug a pipeline, and reason about accuracy, speed, and extrapolation risk with a senior domain engineer. Experience owning the tools or interfaces through which technical work reaches its users, as a means to getting real science into customers' hands. Motivation for this specific job. This role is commercial problem-solving with real science. We will assess for wanting exactly this. Nice to Have Domain studies at engineering depth: CFD and conjugate heat transfer, power-system studies (grid interconnection for large loads including ride-through, protection, power-electronics dynamics of UPS, BESS, and converters), FEA, or electrochemical modeling, with the tools of the domain. Experience with open-source simulation codes (OpenFOAM, OpenDSS, pandapower, CalculiX, or comparable) rather than only commercial packages. Domain experience in energy, infrastructure, or other industrial verticals. Forward-deployed or solutions leadership at a company that scaled the function significantly. How We Work 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. Location and Compensation This is an in-person role based in Boston. We offer competitive compensation including salary, benefits, and meaningful early-stage equity. We evaluate on delivery track record, technical depth, applied scientific judgment, and the quality of the teams you have built. We are an equal opportunity employer and value diverse perspectives in building platforms for AI-driven discovery.