Physical Superintelligence
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. We are seeking engineers to build platform infrastructure at the intersection of computational science, AI systems, and software engineering.
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.
Use this application if you are an engineer, no open engineering role fits your profile, and you want to be considered anyway. We hire excellent engineers when we find them, whether or not a matching role is open. Tell us how your background and ambitions intersect with our mission, and where you would have the most impact.
Our platform spans distributed systems, data infrastructure, agent systems and evaluation, HPC and scientific computing, developer platforms, product engineering, cloud infrastructure, and security. This application is for engineers who are strong across most of that list, or unusually deep in something important we did not list. The bar here is higher than any single posting.
The standard is the same as every engineering role here: full ownership from spec to ship to on-call, and systems other people build on.
Be specific about where you would have the most impact and what you would work on first.
We review these applications on a rolling basis and respond only when we see a strong fit.
A track record of shipping substantive engineering work: systems that shipped and mattered, open source people depend on, infrastructure that outlived your tenure. We weight evidence over credentials.
Depth in several of the areas above and the range to move between them, or singular depth in something important we did not list.
You can walk us through a hard technical decision you made, what you traded away, and what you would do differently.
A concrete reason to be here. If AI systems and physical science together is why you are applying, say so specifically.
Background in any of our named areas: distributed systems, data infrastructure, agent systems and evals, HPC and scientific computing, developer platforms, product engineering, infrastructure, or security.
Experience in research or scientific computing environments.
Something we can read or run: a design doc, a paper, a repo, a postmortem.
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 role is based in Boston. We will consider remote candidates on a case-by-case basis. We offer competitive compensation including salary, benefits, and meaningful early-stage equity. We evaluate on technical breadth, systems thinking, scientific curiosity, and shipping velocity. We are an equal opportunity employer and value diverse perspectives in building platforms for AI-driven discovery.
Anywhere in the World
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