Machine Learning Scientist, Computational Pathology

Your models help cancer patients. This isn’t AI for generating cat videos or customized emojis. Our work directly affects patients who are experiencing among the most difficult periods of their lives. 

Foundation-model scale. We train our own pathology foundation models from scratch with distributed multi-node GPU training on AWS. While frontier labs may have cracked coding and math, their ability to read biology for our problems is unusable. Artera is working on the cutting edge of this space.

Build and evaluate AI models that predict patient outcomes and treatment benefit from whole-slide images and clinical data, or infer molecular traits directly from slides.

Push the frontier in terms of our pan-cancer self-supervised pathology foundation models.

Manage coding agents to propose and execute experiments, improve the efficiency of our tooling, and identify biological insights that explain our models' behavior.

Review findings with product, medical, and biostatistics teams, and contribute to regulatory documentation that gets models into patients’ hands.

Co-author papers and share your work at conferences.

1+ years building deep learning models (we use PyTorch), in industry or in substantial graduate research

Hands-on experience with coding agents like Cursor or Claude Code

Experience taking models beyond a notebook and evaluating them rigorously on messy, real-world data

A background in oncology, biology, or biomedical science, from coursework, research, or work (e.g., a biology or bioengineering degree, computational biology research, or ML work in healthcare or biotech)

Clear communication and an interest in working closely with product, medical, and biostatisticians