(Senior) Scientist, Machine Learning

What you'll do

• Develop and evaluate ML methods, featurization pipelines, and rigorous benchmarks for molecular and chemoproteomics data.
• Apply and refine foundational and generative models to support compound design and prioritization with medicinal chemistry teams.
• Curate scientific datasets, collaborate across research and engineering teams, and communicate findings.

What they ask for

• 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 of industry experience.
• Experience with quantum chemistry, DFT, electronic structure methods, or post-DFT descriptors.
• Experience building molecular ML models and applying generative models, molecular design models, or active learning to drug discovery or chemistry optimization.
• Experience with model evaluation and validation, scientific dataset curation and analysis, and collaboration with medicinal chemistry teams.

Nice to have

• Proficiency with Python, PyTorch, PyTorch Geometric, DGL, RDKit, ORCA, Gaussian, Q-Chem, or related tools.
• Experience with covalent chemistry, reaction modeling, structure-based design, or chemoproteomics data; relevant publications or preprints are a strong plus.

Pay

$180,000 - $258,500 USD base salary

Tools

Python, PyTorch, PyTorch Geometric, DGL, RDKit, ORCA, Gaussian, Q-Chem

AI focus

Develop and apply machine learning and generative models for covalent drug discovery, molecular design, and analysis of chemoproteomics and quantum chemistry data.