Machine Learning Engineer
Computational Drug Discovery
On-siteOn-siteFull-time$140k – $220k / year
About this role
5AM Ventures - Machine Learning Engineer - Computational Drug Discovery
Machine Learning Engineer - Computational Drug Discovery
Watertown, MA
4:59 Initiative – 4:59 Stealth Company /
Full-time /
On-site
apply for this job
Our team is dedicated to the development of a broad pipeline of small molecules powered by unique chemistry insights to address a wide range of highly unmet clinical needs. Our company was created within 5AM Ventures' 4:59 Initiative in 2023. The computational team has roots from D. E. Shaw Research, one of the most rigorous computational science environments in the world. You will work directly with and learn from scientists who have operated at the frontier of computational drug discovery.
Your Role
This role sits at the intersection of machine learning research and the experimental teams that rely on computational tools to drive scientific decisions. Your primary responsibility will be ensuring that cutting-edge models move from research into production—reliably, maintainably, and in forms that scientists can effectively use.
For the right candidate, this is an unusually high-impact position. The systems you build will directly influence molecule triage, experimental prioritization, and the pace of scientific discovery. At many organizations, engineers are several layers removed from scientific decision-making. At our team, that distance is effectively zero.
We value ownership, initiative, and execution. Strong performers will have opportunities to grow into areas such as machine learning research, cheminformatics, AI-driven drug discovery, or agent development. The exact trajectory is flexible and can be shaped around individual strengths and interests.
Your Responsibilities
- Own and maintain production machine learning infrastructure, ensuring models developed by the research team are robust, maintainable, and deployable
- Develop computational tools, data pipelines, and machine learning systems that support scientifi