Scientific Machine Learning Engineer
Core
Build computational workflows combining machine learning with chemical physics to evaluate billions of potential drug molecules and optimize hit discovery campaigns.
Role type
Applied ML engineer (computational chemistry)
Builds
Scalable software for ML virtual screening pipelines integrating with physics-based backends
Domain
Biopharma / Computational Chemistry
Deliverable
production ML models
Required skills
Python, PyTorch, Reinforcement Learning, Active Learning, software development
Preferred skills
Molecular dynamics simulation, free energy calculation, ligand-based drug design, cheminformatics, quantum mechanics, virtual screening
Responsibilities
Design and test scalable software for ML virtual screening pipelines; adapt existing workflows for new discovery cases; benchmark novel ML approaches to improve accuracy
Seniority
Mid-level, hands-on IC
