(Senior) Machine Learning Scientist
Flagship Pioneering · Watertown, MA USA
About this role
**(Senior) Machine Learning Scientist** **Company Overview** Abiologics, Inc. is a privately held, early-stage biotechnology company on a mission to make biology better through an innovative therapeutic modality. We are pioneering **Synteins™**, a transformational class of macromolecular medicines unlocked by novel synthetic and computational technologies. **About the role** We are hiring a **Machine Learning Scientist** to train, validate, and ship 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. In your first year, success means **two or three models in production use** by project teams, each with **documented benchmarks**, **calibrated uncertainty**, and a **clear applicability domain**. **What you will do** - Train and maintain ML models for **ADMET** and developability endpoints (e.g., solubility, permeability, metabolic stability, toxicity, 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, 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; quantify uncertainty and applicability domain - Package models for the platform with engineers (versioned, reproducible, monitored for drift) - Present results and model limits to chemists and project teams; incorporate feedback into retraining **What you bring** - **PhD** in computational chemistry, cheminformatics, machine learning, or related field; or **MS + equivalent industry experience** (~3–6 years hands-on modeling) - Demonstrated experience training/validating ML models on chemical/molecular data (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/temporal splits, baselines, noisy-label handling, uncertainty estimation) - Clear communication with chemists and biologists **Nice to have** - Publications, open-source contributions, or competition results in molecular ML - Experience with generative design, active learning, or Bayesian optimization loops - Experience with large-scale training, MLOps, and model serving - Familiarity with docking, free-energy methods, or protein structure prediction tools - Experience working with biologics or non-small-molecule modalities **Compensation (salary range)** $132,000 – $258,500 (depends on qualifications, skills, competencies, and experience). Abiologics offers healthcare coverage, annual incentive program, retirement benefits, and other benefits.
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