Machine Learning Scientist/Senior Machine Learning Scientist - Synthesis Planning and Optimization, AI for Drug Discovery
Roche
Summary
Join the small-molecule team within AI for Drug Discovery (AI4DD), formerly Prescient Design, at Roche and Genentech's Computational Sciences Center of Excellence as a Machine Learning Scientist / Senior Machine Learning Scientist in Synthesis Planning and Optimization. You will build ML methods that design molecules we can actually make — closing the loop between generative design and automated synthesis.
Job description
The Opportunity
- Develop and advance machine learning methods for synthesis-aware molecular design across retrosynthesis, synthesis planning, molecular generation, and search in synthesizable chemical spaces.
- Integrate proprietary reaction and biochemical data to design the next generation of synthesis-aware models and workflows for hit finding and optimisation.
- Build robust, scalable pipelines for active-learning loops that interface directly with automated and high-throughput synthesis platforms.
- Design novel batch synthesis-planning algorithms that maximise chemical-space coverage, information gain and experimental efficiency.
- Drive scientific impact through publications, open-source releases, and conference talks.
- Collaborate widely with computational and experimental researchers at Roche and with academic partners.
Who you are
- You bring deep machine-learning expertise with a strong foundation in linear algebra, probability and optimization, and hands-on experience in modern machine learning approaches such as graph-neural networks, sequence/language models and reinforcement learning.
- You are familiar with chemistry concepts relevant to synthesis planning and molecular optimisation as well as small molecule data and cheminformatics toolkits such as RDKit or Openeye.
- You are fluent in Python and have experience with modern ML frameworks like PyTorch or JAX as well as scientific software development.
- You hold a PhD or equivalent research depth in machine learning, computational chemistry, chemical engineering or a related quantitative field such as physics or statistics, with up to 2 years of industry research experience (Scientist) or 2+ years of industry research experience (Senior Scientist).
- You have a record of scientific excellence evidenced by journal and conference publications or a public portfolio of relevant projects (e.g. hosted on GitHub/GitLab).
Preferred
- Experience with retrosynthesis or synthesis-planning models.
- Experience with automated/high-throughput synthesis.
Requirements
- Deep machine-learning expertise with a strong foundation in linear algebra, probability and optimization
- Hands-on experience in modern machine learning approaches such as graph-neural networks, sequence/language models and reinforcement learning
- Familiarity with chemistry concepts relevant to synthesis planning and molecular optimisation
- Familiarity with small molecule data and cheminformatics toolkits such as RDKit or Openeye
- Fluent in Python
- Experience with modern ML frameworks like PyTorch or JAX
- Experience with scientific software development
- PhD or equivalent research depth in machine learning, computational chemistry, chemical engineering or a related quantitative field such as physics or statistics
- Up to 2 years of industry research experience (Scientist) or 2+ years of industry research experience (Senior Scientist)
- Record of scientific excellence evidenced by journal and conference publications or a public portfolio of relevant projects
Benefits
- Discretionary annual bonus
Company overview
Roche is a Swiss multinational healthcare company and a global pioneer in pharmaceuticals and diagnostics, founded in 1896 and headquartered in Basel, Switzerland. As the world's largest biotech company and the fifth-largest pharmaceutical company by revenue, Roche operates through two primary divisions: Pharmaceuticals and Diagnostics. The company is renowned for its leadership in personalized healthcare, combining strengths in both drug development and diagnostic testing to deliver tailored treatments for patients. Roche maintains a strong focus on oncology, immunology, infectious diseases, ophthalmology, and central nervous system disorders, with a portfolio that includes over 30 medicines on the World Health Organization's Model Lists of Essential Medicines. The company owns significant subsidiaries including Genentech, Chugai Pharmaceuticals, Ventana Medical Systems, and Foundation Medicine. With approximately 103,000 employees worldwide and operations in over 100 countries, Roche has established itself as a leader in cancer treatments globally while maintaining a robust pipeline of innovative therapies and diagnostic solutions. The company's commitment to sustainability has been recognized through ten consecutive years as Group Leader in the Dow Jones Sustainability Indices within the Pharmaceuticals, Biotechnology & Life Sciences Industry.