We're building AI capable of autonomous scientific discovery. Our mission is to reach a world where discovery is no longer bottlenecked by the number of human scientists alive to pursue it.
Reinforcement learning has taken models remarkably far in math and code, where an answer can be checked and a model can learn from ten thousand attempts. Science offers no such reward function. The judgment a scientist exercises before any result is certain, which hypothesis is worth the month, what the evidence actually supports, when to abandon a promising dead end, has never been captured at scale. That missing signal is the real bottleneck, and it's the one we build for: the environments, datasets, and expert reasoning that teach models to do science, not just recite it.
That work is already in the world. We built and operate Aristotle, an AI research partner trusted by thousands of researchers at some of the most demanding institutions in science, including GSK, Pfizer, AstraZeneca, Merck, Stanford, MIT, Harvard, and the FDA. Alongside it, we're developing autonomous research systems that take on long-horizon scientific problems end to end.
Backed by leading investors and advised by the scientists who built the field, Autopoiesis is redefining what discovery looks like in the most important industry of the century.
We're looking for exceptional interns to work alongside our research team on the core problem of training models that can do science on their own. This is a real research and engineering role, not a shadowing exercise. You'll take on genuine problems, run experiments, build the systems around them, and see your work make it into what we're building.
We don't draw a hard line between research and engineering, and we don't want interns who do either. What matters is that you can form a hypothesis, build the thing that tests it, read the results honestly, and decide what to do next.
We run internships in three cohorts, Fall 2026, Spring 2027, and Summer 2027. Each is a 12-week paid internship, in person at our San Francisco office.
Everything we do either moves discovery forward or it doesn't, and anything that doesn't is a day we won't get back. We hold every decision, every hire, and every week against that one question. The mission is hard enough that nothing else earns a place next to it.
We think in expected value. A good decision made on the best available information is a good decision even when the result disappoints, and a lucky win off a bad process teaches us nothing. We reward sound reasoning, run the bets worth running, and judge ourselves by how well we chose, not only by how it landed.
Competition is a symptom of a weak position. We don't win by racing others down a crowded path, we win by building something no one else can, in a direction no one else is looking. When we find ourselves fighting for scraps, we've made a strategic mistake upstream.
There are no bystanders here. We spot what's broken, take full responsibility for a strong result, and see it through. We're self-driven, own our mistakes plainly, and feel deep responsibility for what we're building.
We are hiring for this position in our San Francisco office. We are in person 5 days a week.
A 12-week paid internship working directly on the core problem of getting AI to make real scientific discoveries, alongside a young team moving fast on one of the most important problems in science. If you want to find out what work at the frontier feels like, even if you don't meet every requirement.
Autopoiesis Sciences, Inc. is an equal opportunity employer committed to diversity and inclusion. We welcome applications from all qualified candidates regardless of race, gender, age, religion, sexual orientation, or any other legally protected characteristics.
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