onsite
Machine Learning Scientist - Synthesis Planning & Optimization - Roche
ML Engineer
Lead the development of advanced ML models that bridge generative design and automated synthesis, optimizing small‑molecule production pipelines using Python, deep learning, and chemoinformatics tools.
About the role
Key Responsibilities
- Design, implement, and validate machine learning models that predict synthetic feasibility and optimize reaction routes for novel molecules.
- Integrate generative chemistry outputs with automated synthesis workflows, ensuring end‑to‑end manufacturability.
- Collaborate with chemists, data scientists, and software engineers to refine model performance and deploy solutions in production.
- Analyze large chemical datasets, engineer features, and develop evaluation metrics tailored to synthesis planning.
- Publish findings in internal reports and external conferences, contributing to the broader AI4DD knowledge base.
Requirements
- PhD or equivalent experience in chemistry, chemical engineering, computer science, or related field.
- Proven expertise in machine learning, especially deep learning for molecular data.
- Strong programming skills in Python and experience with RDKit, PyTorch/TensorFlow.
- Experience with synthesis planning tools and knowledge of reaction databases.
- Excellent communication skills and ability to work cross‑functionally in a fast‑paced environment.
Skills
machine learningpythondeep learning