Senior Scientist, Artificial Intelligence/Machine Learning, Foundational ML (gCS, BRAID)

$165,200 - $306,800/Yr

Genentech - South San Francisco, CA

Full-time - Senior

South San Francisco, CA

Chemical Manufacturing

About the position

Genentech seeks a highly motivated Senior AI Scientist to join the Deep Learning Theory and Algorithms (DELTA) lab within the BRAID (Biology Research | AI Development) department in Genentech Research and Early Development (gRED). Our lab is dedicated to advancing deep learning research to support drug discovery and target discovery efforts, with a focus on large-scale foundation models in research biology. We are committed to driving innovation through cutting-edge ML methods with real-world impact in the drug discovery field. In this role, you will lead and execute a research program that develops novel foundational deep-learning methods with the ultimate aim of contributing to the drug discovery process. You will work in an exciting and multidisciplinary environment alongside AI scientists, ML engineers, computational biologists, and biological chemists, working on different areas of biology and chemistry. Your responsibilities will include leading the research, design, and execution of novel, cutting-edge ML research with applications to drug discovery and target discovery. You will drive novel research on foundational AI methods for scientific problems, with a specific focus on foundation models, large-scale representation learning, and generative methods. This involves scaling ML models to large biological datasets, working at the intersection of deep learning and engineering challenges to support new scientific questions. You will also be expected to regularly publish in top-tier ML venues (e.g., NeurIPS, ICLR, ICML, AISTATS, etc.) and scientific journals, presenting results at internal and external scientific venues, conferences, and workshops. Collaboration with interdisciplinary and cross-functional teams across gRED will be a key aspect of your role.

Responsibilities

• Lead and execute a research program developing novel foundational deep-learning methods for drug discovery.
• Collaborate with AI scientists, ML engineers, computational biologists, and biological chemists.
• Design and execute cutting-edge ML research with applications to drug discovery and target discovery.
• Drive research on foundational AI methods focusing on foundation models and large-scale representation learning.
• Scale ML models to large biological datasets and address engineering challenges.
• Publish research findings in top-tier ML venues and scientific journals.
• Present results at internal and external scientific venues, conferences, and workshops.

Requirements

• PhD or equivalent experience in machine learning or related technical field.
• Excellent knowledge of the theory and practice of deep learning, demonstrated through past projects and publications.
• Strong publication record at top-tier ML venues such as NeurIPS, ICML, ICLR, AISTATS.
• Excellent Python and PyTorch programming skills with knowledge of software engineering best practices.
• Strong communication and collaboration skills.

Nice-to-haves

• Experience in developing and applying deep representation learning methods (e.g., generative, contrastive, graph-based).
• Interest in biochemical drug discovery.

Benefits

• Discretionary annual bonus based on individual and company performance.
• Comprehensive health benefits including medical, dental, and vision insurance.
• 401(k) retirement savings plan with company matching contributions.
• Paid time off and holidays.
• Professional development opportunities and support for continuing education.