# Applied ML Scientist (Staff / Principal) at Genesis Therapeutics

- Company: Genesis Therapeutics
- What the company does: Genesis pairs frontier AI with world-class drug hunters to discover small molecule medicines. Built on Pearl and GEMS. Partnered with Gilead and Incyte. Backed by a16z.
- Company website: https://www.genesis.ml
- Type: Startups (AI role)
- Level: Principal and up
- Location: San Mateo, CA
- Work setup: Remote
- Posted: 2026-05-19
- Apply by: 2026-10-08
- Apply: https://jobs.ashbyhq.com/genesis-molecular-ai/b239a6b5-40f2-41fd-93e6-3b7ca2c7eac7
- Page: https://www.1752.vc/careers/jobs/genesis-therapeutics-applied-ml-scientist-staff-principal/

## About the role

This unique role is for a scientist who is passionate about being a catalyst for applying cutting-edge AI to solve real-world drug discovery challenges. You will be the critical bridge between our long-term research and our experimental drug discovery programs. Your mission is to build, evaluate, monitor, and improve our state-of-the-art models directly into active drug programs, leading the charge on model validation, deployment, and analysis to guide the discovery of new medicines.

## What they're looking for

- A seasoned computational scientist with a proven track record of machine learning based methods to impact small molecule drug discovery projects
- A cheminformatics expert , fluent in the language of molecular data with hands-on mastery of tools like RDKit or OpenEye
- A scientist who speaks the language of experimental drug discovery, with a strong familiarity with common assay types (biochemical/binding/cell-based assays, in vivo studies, etc.) and CADD workflows (docking, virtual screening, ADME prediction, etc.)
- A rigorous data scientist, with experience inmodeling and analysis of small molecule datasets and passion for statistical validation, uncertainty quantification, and deriving clear insights from complex, noisy data
- A hands-on applied scientist and software engineer with strong coding skills in Python and a deep practical knowledge of the applied ML toolkit (e.g., scikit-learn, PyTorch)
- An exceptional communicator and collaborator , able to act as the bridge between machine learning researchers and experimental scientists

Tags: AI