Senior ML Scientist - Molecular Design & Drug Discovery

Pioneering Medicines; Massachusetts; Vor Ort; USD 132.000 - 259.000; Vollzeit

Zusammenfassung

Abiologics, Inc. in the United States seeks a Machine Learning Scientist to train, validate and ship predictive models powering our molecular design platform.

You will build models scoring molecules for ADMET, potency and synthesizability, working with chemists, biologists and platform engineers. In your first year, expect several models in production with benchmarks, uncertainty estimates and clear applicability domain.

Qualifikationen

• PhD in computational chemistry, cheminformatics, machine learning or related field, or an MS plus equivalent industry experience.
• Experience training and validating ML models on chemical data, in industry or academia, with shipped or published results.
• Direct experience with at least two of: ADMET/developability, potency/binding, synthesizability/retrosynthesis, protein or ligand structure.
• Fluency with molecular representations (fingerprints, descriptors, graphs, 3D) and tools such as RDKit.
• Strong Python and a deep learning framework (PyTorch preferred); experience with GNNs or transformers on molecules.
• Rigorous evaluation habits: scaffold or temporal splits, baselines, noisy-label handling and uncertainty estimation.
• Clear communication with chemists and biologists.

Aufgaben

• 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.
• Package models for the platform with engineers: versioned, reproducible and monitored for drift.
• Present results and limits of each model to chemists and project teams, and incorporate their feedback into retraining.

Kenntnisse

Python

PyTorch

RDKit

GNNs

Transformers

Uncertainty estimation

Communication

Cheminformatics

Ausbildung

PhD in computational chemistry, cheminformatics, machine learning or related field

MS + equivalent industry experience

Tools

RDKit

Jobbeschreibung

Abiologics, Inc. in the United States seeks a Machine Learning Scientist to train, validate and ship predictive models powering our molecular design platform.

You will build models scoring molecules for ADMET, potency and synthesizability, working with chemists, biologists and platform engineers. In your first year, expect several models in production with benchmarks, uncertainty estimates and clear applicability domain.