At Roche's AI for Drug Discovery (AIDD) group (formerly Prescient Design), we are revolutionizing drug discovery with cutting-edge machine learning techniques. We are seeking talented researchers and engineers with a passion for building machine learning systems that transform how scientific data is represented, modeled, and evaluated. AIDD’s Foundation Model team is seeking a Machine Learning Research Intern to work on data interfaces between structured biochemical measurements and large language models, supporting next-generation foundation models for drug discovery as part of our broader Lab-in-the-Loop approach. The intern will collaborate closely with researchers and engineers to design, implement, and evaluate data transformation and modeling pipelines, gaining hands-on experience with real-world scientific datasets and foundation-model workflows. This role is well suited for candidates who enjoy careful technical reasoning, experimentation, and building reusable components that sit at the intersection of machine learning and scientific data. The group provides a dynamic and challenging environment for multidisciplinary research, including access to heterogeneous data sources, close links to top academic institutions around the world, as well as collaborations with internal Genentech and Roche teams. This internship position is located in New York City, NY, On-Site.