Adaptyv is building an automated lab that lets AI agents run biology experiments.
We're entering the era of agentic science where AI models can now design novel proteins, propose hypotheses, and iterate on experimental results. But they can't run the experiments themselves - that's still a manual, months-long process. We're building the infrastructure that gives AI agents access to the physical world.
We are one of the fastest growing biotech companies, trusted by leading biopharmas, frontier AI labs, and the techbio companies pushing the field forward. This is a rare chance to help advance some of the most important work happening in biotech today.
Our automated lab is powered by a deep software + hardware stack: lab instruments worth millions of USD reverse-engineered into API-controllable hardware, dozens of devices orchestrated through complex workflows, full observability on everything that happens in the lab, processing pipelines for messy physical-world data, and AI systems that troubleshoot production results and accelerate assay development.
We’re growing rapidly and are hiring for talented people to scale and support the massive demand for AI-driven wet lab experimentation.
This is an internship for an exceptional student or early-career builder — your shot to do the most serious work of your life so far, on a small team where interns own real problems.
Building an automated lab throws off an endless stream of problems, and they don't respect job titles. One week it's a gnarly data pipeline, the next a misbehaving instrument, a model that needs evaluating, or a supplier bottleneck blocking production. We'll point you at the ones that fit you, give you a senior person to learn from, and expect you to make a real dent. The goal is simple: create obvious, measurable value. Do that, and this doesn't have to end as an internship — if you're good, you stay.
Depending on where you're strongest and where we need you, any of:
Software / ML — internal tools, data pipelines, automation scripts, model evaluation, agents.
Lab automation — getting instruments talking, debugging work cells, building hardware glue.
Biology — hands-on in the lab, supporting and improving production workflows.
Operations / logistics — untangling supplier, inventory, or process bottlenecks.
You'll go deep on one or two of these — not all. We care that you're excited the list is this wide and that you learn new domains fast.
A student or recent grad — or someone early in their path who hasn't found the right box yet. This is explicitly an early-career role.
Show us something you've built. A project, repo, paper, hack, side business, competition win — proof you make things and don't wait for permission. A strong application leads with this, not with your transcript.
Quick on your feet. You walk into an unfamiliar problem, work out what matters, and start making progress on your own.
A fast learner who's genuinely generalist. You pick up new domains quickly and aren't precious about which kind of problem you work on.
AI-native. It's 2026 — you build with coding agents like Claude Code as a default and get far more done because of it.
High energy, high agency. You see what needs doing and do it.
When you apply, lead with the single most impressive thing you've built so far and a link to it.
We review applications on a rolling basis.
Application deadline
We are reviewing applicants on a rolling basis.
