Machine Learning Scientist/Senior Machine Learning Scientist – Agents for Applied Small Molecule Drug Design, AI for Drug Discovery Full-time NEW

Machine Learning Scientist / Senior Machine Learning Scientist

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 building agents for applied small-molecule drug design. You will develop autonomous, LLM-driven agentic workflows that orchestrate ML models, physics-based methods, and cheminformatics tools to accelerate discovery, working with world-class chemists and structural biologists.

The Opportunity:

• Design, build, and apply agentic workflows and ML models for key challenges in small-molecule drug design.
• Fine-tune foundation models for drug discovery relevant topics using internal and external datasets and tools.
• Optimize agent-derived hypotheses in close collaboration with world-class computational and medicinal chemists and structural biologists.
• 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 are experienced developing LLM-driven agents for scientific workflows and you understand how to orchestrate tools and models reliably.
• You bring strong machine-learning foundations in linear algebra, probability and optimization, with hands-on experience with GNNs, sequence/language models and reinforcement learning.
• You are fluent in Python and modern agentic coding environments such as LangChain, ML frameworks such as PyTorch or JAX, as well as cheminformatics toolkits like RDKit or OpenEye.
• You hold a PhD or equivalent research depth in machine learning, computer science, chemical engineering or a related quantitative field such as physics or statistics.
• 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:

• Hands-on experience orchestrating multi-tool or multi-agent scientific pipelines.
• Hand-on experience working along the small molecule drug discovery value chain and an excitement to engage with chemists.
• Familiarity with structural biology datasets.

If you want to put autonomous AI to work discovering the medicines patients need next, apply now and help build the future of drug design at Roche.