Machine Learning Scientist - Quantum Chemistry

Overview In this role, you apply machine learning to quantum chemistry to power small-molecule drug discovery. You will work in a collaborative AI for Drug Discovery team to build fast, accurate models of energetics and protein–ligand interactions. You’ll create synthetic datasets and deploy scalable pipelines that feed Roche’s molecular-design tools. Expect opportunities to publish, share open-source work, and present at conferences. This position offers meaningful impact through advancing quantum-ML methods in a leading pharma environment.

Verantwortungsbereiche Develop ML models that integrate quantum chemistry for small-molecule energetics and binding free energy Create synthetic datasets using quantum mechanics to guide research directions Build robust, scalable, and reproducible deployment pipelines feeding molecular-design tools Collaborate with computational and experimental teams and academic partners Drive scientific impact through publications, open-source releases, and talks Zentrale Anforderungen Deep ML expertise with solid foundation in linear algebra, probability and optimization Hands-on quantum chemistry experience Fluency in Psi4, PySCF and ORCA; experience with xTB Proficiency in Python and ML frameworks (PyTorch or JAX) PhD or equivalent in a relevant field Track record of publications or a public project portfolio (GitHub/GitLab) Collaborative mindset; strong cross-functional communication Curiosity and

ability to translate scientific results for broader audiences ability to work in a fast-paced, innovative environment Machine learning theory and model development Quantum chemistry toolkits (Psi4, PySCF, ORCA) Semi-empirical methods (xTB)