Senior Scientist, AI-Driven Antibody Design & Discovery

Genentech; South San Francisco (CA); On-site; USD 201,000 - 374,000; Full time

Benefits offered by this job

Discretionary annual bonus

Job summary

Genentech, part of Roche, is seeking a senior scientist-leader in AI for Drug Discovery within the Computational Sciences Center of Excellence. You will drive portfolio applications of machine learning for developability and antibody design, influencing active gRED projects and collaborating across discovery teams.

You will mentor a team of computational scientists, shape research direction, and communicate complex results to senior leadership while aligning with pRED counterparts.

Qualifications

• PhD with 10+ years total experience, 5+ in ML/computational methods for biologics.
• Experience translating computational work into portfolio impact.

Responsibilities

• Lead portfolio applications of ML models to active gRED projects with measurable outcomes.
• Serve as technical advisor to gRED leadership on computational strategy and capability development.
• Lead the Large Molecule portfolio modeling team, mentor scientists and set research direction.
• Develop and execute a technical strategy for ML in antibody discovery and engineering.
• Navigate stakeholder landscapes to align priorities and foster collaboration.
• Identify and own high-impact research initiatives advancing portfolio science.

Skills

Large molecule design

Antibody engineering

Biophysical modeling

Developability assessment

Translating research to portfolio

Communication with leadership

Education

PhD in Computational Biology/Biophysics/Immunology/Chemistry/CS

Tools

Computational ML methods

Job description

Genentech, part of Roche, is seeking a senior scientist-leader in AI for Drug Discovery within the Computational Sciences Center of Excellence. You will drive portfolio applications of machine learning for developability and antibody design, influencing active gRED projects and collaborating across discovery teams.

You will mentor a team of computational scientists, shape research direction, and communicate complex results to senior leadership while aligning with pRED counterparts.