Machine Learning Scientist

Responsibilities

• Design, implement, and improve large-scale distributed machine learning systems and core infrastructure.
• Develop strategies to improve model performance on scientific tasks, including complex reasoning and long-horizon task completion.
• Translate biological and chemical domain knowledge into machine learning objectives, training signals, and evaluation criteria.
• Design evaluation methodologies and benchmarks to assess model capabilities relevant to biological research.
• Collaborate with researchers to translate prototypes into scalable, production-ready systems.
• Maintain training infrastructure and data pipelines to ensure reliable experiments on clusters.

Requirements

• BS/MS in Computer Science, Statistics, Mathematics, Physics, or a related quantitative field with 2+ years of relevant work experience, or a PhD with 0-2 years of experience.
• Experience developing and training large-scale machine learning models.
• Expertise in post-training techniques to enhance reasoning, alignment, and domain knowledge.
• Strong software engineering skills and experience with high-performance computing systems.
• A strong history of research excellence with publications at top-tier venues (e.g., NeurIPS, ICLR, ICML).

Preferred Qualifications

• Experience working with molecular modalities such as protein sequences, chemical graphs, or structured molecular data.
• A public portfolio of research or significant contributions to open-source machine learning libraries.
• A passion for applying frontier AI technologies to the field of drug discovery.

About the Company

Genentech, a member of the Roche group, is a pioneer in the biotechnology industry. We are dedicated to pursuing groundbreaking science to discover and develop medicines for people with serious and life-threatening diseases. Our AI for Drug Discovery (AIDD) group leverages cutting-edge machine learning to revolutionize the way medicines are designed and developed.