- Watertown, Massachusetts, United States
- Full-time · Senior
- $132K–$259K per year
- 3–6 years
We are hiring a Machine Learning Scientist to train, validate and ship the predictive models that power our molecular design platform. You will build models that score chemical molecules for developability (ADMET), potency, synthesizability and 3D structure, working alongside chemists, biologists and platform engineers.
Compensation
The salary range for this role is $132,000 - $258,500.
Responsibilities
- Train and maintain ML models for ADMET and developability endpoints such as solubility, permeability, metabolic stability, toxicity and aggregation risk.
- Build potency and binding models (QSAR, ligand- and structure-based) to rank and prioritize molecules against targets.
- Develop synthesizability models: synthetic accessibility scoring, reaction-outcome prediction and retrosynthesis-informed filters.
- Apply and fine-tune structure-aware models (GNNs, equivariant networks, protein-ligand structure and docking-informed ML).
- Curate and clean assay data, define scaffold- or time-split benchmarks, and quantify uncertainty and applicability domain.
Requirements
- PhD in computational chemistry
- cheminformatics
- machine learning
- or related field
- MS plus equivalent industry experience