Senior / Principal Machine Learning Scientist, Scientific Reasoning Models

About the role

Roche's AI for Drug Discovery (AIDD) group, Prescient Design, is looking for a Senior or Principal Machine Learning Scientist to join its Foundation Models team. You will drive the development of internal reasoning Large Language Models (LLMs) for drug discovery tasks such as biomolecular design, working at the intersection of engineering and research to design and scale large machine learning systems.

Key responsibilities

• Lead the design and evolution of scientific reasoning systems, setting technical direction for model architectures, training strategies and evaluation methods.
• Define and run approaches to improve model performance on scientific tasks, including long-horizon reasoning and complex decision-making.
• Translate biological and chemical domain knowledge into machine learning objectives, training signals and evaluation criteria, working with domain experts.
• Architect and improve large-scale distributed machine learning systems, ensuring robustness, efficiency and reproducibility.
• Partner with researchers and cross-functional teams to move models from research prototypes to production-ready systems supporting active discovery programs.
• As Senior: implement scientific reasoning, own end-to-end large-scale training runs and mentor junior staff and interns. As Principal: define the long-term technical roadmap, architect initiatives integrating diverse data modalities and advise leadership on using generative AI in the therapeutic pipeline.

Required profile

• PhD in Computer Science, Statistics, Mathematics, Physics or a related quantitative field.
• Senior (SE6): 0-2+ years of industry or post-doc experience focused on deep learning.
• Principal (SE7): 5+ years of industry or post-PhD experience with a track record of technical leadership and project ownership.
• Extensive experience developing and training large-scale models, including improving domain understanding, reasoning and model alignment.
• Strong publication record at top-tier venues (e.g. NeurIPS, ICLR, ICML).
• Preferred: experience with molecular modalities (protein sequences, chemical graphs, structured molecular data), a public research portfolio or open-source ML contributions, and a passion for applying frontier AI to drug discovery.

Required skills

• Deep learning and large-scale model training
• Large-scale distributed machine learning systems
• Software engineering

Relocation benefits are not available. The expected salary range depends on location: for New York City, $160,100-$297,300 for the Senior Scientist and $185,600-$344,600 for the Principal Scientist. A discretionary annual bonus may be available.