(Senior) Scientist, Machine Learning

The role

This person will develop, evaluate, and apply machine learning approaches to connect chemoproteomics data with quantum chemistry and generative molecular design. They will contribute to an AI platform for covalent drug discovery by linking experimental data to physical features.

What you will do

• Develop, implement, and evaluate innovative machine learning methods
• Design and implement rigorous benchmarks to evaluate model performance
• Refine, fine-tune and apply foundational models to drug discovery programs
• Perform hands-on data curation, quality control, and dataset construction
• Develop scalable featurization and modeling pipelines for large molecular datasets
• Collaborate with computational, chemistry, biology, and proteomics teams
• Partner with engineering teams to productionize modeling workflows
• Communicate technical findings and scientific implications across teams

Required qualifications

• Ph.D. in machine learning, computational chemistry, chemical physics, computer science, applied mathematics, or a related discipline with 2+ years of industry experience, or M.S. degree with 6+ years
• Experience with quantum chemistry, DFT, electronic structure methods, or post-DFT descriptors
• Experience building molecular ML models including graph neural networks, geometric deep learning, equivariant architectures, diffusion models, or related approaches
• Experience applying generative models, molecular design models, or active learning workflows to drug discovery or chemistry optimization problems
• Experience working closely with medicinal chemistry teams to prioritize compounds, interpret model outputs, and incorporate experimental feedback into model development
• Experience developing rigorous model evaluation frameworks, benchmarks, and validation strategies for molecular ML or scientific machine learning applications
• Ability to curate, clean, integrate, and analyze complex, large-scale scientific datasets from multiple sources
• Experience with scalable data processing, model training, and analysis workflows for large scientific datasets
• Ability to work closely with experimental scientists and translate biological and chemical questions into computational strategies
• Excellent communication and cross-functional collaboration skills

Nice to have

• Publications or preprints in, e.g., NeurIPS, ICML, ICLR, bioRxiv
• Proficiency with Python and modern ML frameworks such as PyTorch, PyTorch Geometric, DGL, or related tools
• Proficiency with cheminformatics and molecular modeling toolkits such as RDKit, ORCA, Gaussian, Q-Chem, or related software
• Experience with covalent chemistry, reaction modeling, structure-based design, or chemoproteomics data

Benefits

• healthcare coverage
• annual incentive program
• retirement benefits
• broad range of other benefits

About the company

Expedition Medicines is a privately held, early-stage biotechnology company pioneering the emerging field of Protein Editing. It is backed by Flagship Pioneering.