onsite
Machine Learning Scientist - Small Molecule Drug Design - Roche
ML Engineer
Lead the development of AI-driven models for small‑molecule drug discovery, leveraging Python, deep learning, and chemoinformatics tools to accelerate lead identification and optimization.
About the role
Key Responsibilities
- Design, implement, and validate machine learning pipelines for predicting physicochemical properties, ADMET, and bioactivity of small molecules.
- Collaborate with medicinal chemists and computational chemists to integrate experimental data into predictive models.
- Develop and maintain codebases in Python, utilizing libraries such as RDKit, PyTorch/TensorFlow, and scikit‑learn.
- Perform feature engineering, model selection, hyper‑parameter tuning, and rigorous evaluation using cross‑validation and external test sets.
- Document methodologies, results, and best practices; present findings to cross‑functional teams.
Requirements
- Ph.D. or Master’s in Computer Science, Chemistry, Bioinformatics, or related field with strong quantitative background.
- Proven experience in applying machine learning to drug discovery or cheminformatics.
- Strong programming skills in Python and familiarity with RDKit, deep learning frameworks, and version control.
- Excellent analytical, problem‑solving, and communication skills.
- Ability to work independently and collaboratively in a fast‑paced research environment.
Skills
pythonmachine learningdeep learning