ML Research Engineer / Scientist (Remote, international)

Medical imaging, 3D, or volumetric data

Vision-language models or self-supervised learning

DICOM, CT, or radiology background

A PhD or publications (a real plus, never a gate)

You do not need prior medical-AI experience. You will learn radiology from the clinicians who read alongside the model every day.

We have FDA-cleared AI: the first commercial system to simultaneously triage seven urgent conditions on abdomen-pelvis CT in the US. From here the path runs to deployment nationally, and soon internationally. We are backed by Khosla Ventures, and we are a small team that ships. Every model you train stays close to the metal: it reaches submissions, deployments, and patients within months. This is the moment clinical AI grows up, and you would have a front-row seat with your hands on the model.

This is a team of builders and researchers. The same people who created CheXpert, CheXZero, and other widely used open datasets and algorithms in radiology AI have shipped FDA-cleared products into live clinical use. Day to day you would work with ML and software engineers, a Kaggle Grandmaster, and fellowship-trained radiologists across chest, body, MSK, neuro, and oncology who read alongside the model. a2z was co-founded by Pranav Rajpurkar, one of the most-cited researchers in medical AI.

Location: Remote (international)

Compensation: Competitive base + equity

Eligibility: Open to candidates worldwide; this role is fully remote.

One question we would love your take on when you apply: tell us about a model you built, and what you would change if you trained it again.