Medical Student Clinical AI Fellow

About us

Alterra Labs is the safety and alignment company for AI in healthcare and the life sciences.

The most capable healthcare AI won’t be the model that gets the most benchmark questions right. It will be the one that can navigate the complexity of real clinical care without missing what matters. Healthcare decisions rarely happen in a clean sequence. Information is incomplete, records conflict, and the right action can depend on something that happened hours, days, or months earlier. A model can perform well on a test and still fail when it has to reason across a real workflow.

That’s why clinicians have to be part of how AI is evaluated, and why it has to happen now. AI is already entering the exam room, the inbox, and the chart. The people who decide what “safe” and “good enough” mean for these systems should be the people who have sat with patients, weighed uncertain evidence, and lived with the consequences of a decision. Being a physician has always meant two commitments at once: to heal the patient in front of you, and to advance what medicine knows for the patients who come after. Holding AI to a clinical standard is a continuation of both. “First, do no harm” applies to the tools we build, not just the care we give.

Alterra builds realistic simulation environments of real healthcare software: EHRs, imaging systems, payer portals, voice, and clinical trials. We seed them with real-world data and pair them with clinician-authored tasks and rubrics. Frontier AI labs, applied AI companies, health systems, and life sciences organizations use our work to see where their models break, why they break, and how to make them better before those failures reach patients.

Our name translates to “another earth.” We’re a team of over 60 clinicians, scientists, ML researchers, and engineers based in New York. We’re backed by Oak HC/FT, Flare Capital Partners, and Company Ventures.

About the role

This is a role for post core clinical rotation medical students.

Clinical Research Fellows are at the center of how we find out where AI fails in medicine. You’ll use your clinical judgment to probe frontier models inside our environments, build tasks that expose where they go wrong, and write the rubrics that grade them. You own your work end to end: from the first idea, through running evals and review by our expert collaborators (attending physicians), to final sign-off.

At Alterra, the reasoning behind an action matters as much as the action itself. A model that solves a task for the wrong reasons has failed it. Your job is to find those failures, explain why they happen, and turn them into the signal that makes models safer and more capable.

This isn’t data labeling. It’s applied clinical research, built as a part-time fellowship that fits alongside training. If you’re curious about how AI will change medicine and want to help set the clinical standard it’s held to, we want to hear from you.

If you join, you will:

• Run frontier models on realistic, multi-step clinical tasks inside our environments and find where they break, such as a model that orders a contrast CT without checking kidney function or allergies.

• Build targeted tasks that isolate a specific failure, grounded in real patient data and real clinical workflows.

• Write rubrics based on clinical guidelines and your own clinical expertise, with clear critical checkpoints that grade model behavior the way an expert clinician would.

• Measure how often each failure occurs and dig into why it happens: the evidence, the mechanism, and the clinical impact.

• Work closely with our attendings who are expert collaborators, both in live sessions and asynchronously, to shape failure modes, review your tasks, and refine your rubrics.

• Collaborate with our broader team of researchers, engineers, and fellow clinicians to turn your findings into work that ships to partners.

We’re looking for you if you have:

• Sharp clinical reasoning. You can synthesize a messy record, notice what’s missing or contradictory, and explain a defensible conclusion.

• Ownership. You follow your work through to the end, surface problems early, and hold a high bar for quality without being asked.

• Curiosity about AI. Prior work with LLMs, model evaluation, red-teaming, or EHR data is a plus but not required. We’ll teach you the pipeline.

• Clinical training. You’re a medical student who has completed core clinical rotations, a resident, or a fellow. We also welcome pharmacists, nurses, clinical informaticists, and clinical trials professionals with operational and systems workflow experience.

• Clear, honest availability. Fellows commit to a multi-month blocks, so we need an accurate picture of your time from the start, including rotations and clinical on-service blocks.

This is a list of ideal qualifications. If you don’t meet every one of them, you should still consider applying. We encourage people from all backgrounds to apply.

How we work

• Two-week research cycles. Each cycle starts and ends on a Monday morning, with clear task goals set at the start.

• Onboarding as a cohort. New fellows start together with a one-time Sunday boot camp covering the full pipeline, from environments to expert sign-off, then go straight into their first cycle.

• Room to grow. Fellows who have more time and show strong work can advance to leading their own research directions.

• What “done” means: A task is complete only after it receives expert sign-off. Some tasks need multiple rounds of review and iteration with our expert collaborators before they get there.

• Commitment: Fellows join for an expected 3–6 month block. They do not have to work every 2 week block, but they need to be clear about when they can work. There are monthly check-ins on fit and performance.

How to apply

After submit your application, you’ll get an email about an assessment. You will need to download and complete an assessment that takes about 60–120 minutes. We’ll will review your application and get back to you about next steps