Vice President, Global Head of AI for Drug Discovery (AIDD)

Genentech • Daly City, CA

19d • $364,140 - $449,820

About The Position

The Vice President and Global Head of AI for Drug Discovery (AIDD) leads an artificial intelligence and machine learning department focused on designing therapeutics across the Roche/Genentech Research and Early Development (RED) portfolio. As a member of the Computational Sciences Center of Excellence (CSCoE) leadership team, this role also advances AI and other computational methods across Research and Early Development at Roche/Genentech.

The role builds, scales, and deploys AI methodologies, models, and computational frameworks for antibody design, protein engineering, and small molecule design. It partners with Discovery, Early Development, Therapeutic Area leads, and Translational teams to apply these methods across the portfolio. The Global Head builds and mentors a global team of AI scientists, machine learning engineers, computational researchers, and their managers, and develops strategic partnerships across gRED, pRED, and the external AI community.

The position is based in New York, San Francisco, or Basel and requires high flexibility and frequent international business travel. The expected salary range for the primary locations of South San Francisco, CA, and New York, NY is $364,140–$449,820. Actual pay depends on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. The position qualifies for benefits detailed at a linked resource. Genentech is an equal opportunity employer and provides an accommodation contact process for applicants with disabilities.

Requirements

• Ph.D. or equivalent advanced degree in Computer Science, Artificial Intelligence, Computational Chemistry, Machine Learning, Computational Biology, or a related quantitative field.
• Familiarity with drug discovery, molecule design, and therapeutic discovery.
• Expertise in modern artificial intelligence, deep learning architectures, and generative models; ideally also molecular modeling and computational drug discovery.
• Demonstrated experience advancing state-of-the-art AI infrastructure.
• Record of leading foundation model or large-scale engineering efforts, or building research groups recognized in the external AI community.
• Demonstrated ability to lead large, multidisciplinary teams and foster global collaboration.
• Exceptional communication skills.
• Ability to thrive in ambiguity and bring clarity to team objectives.
• Ability to define and communicate a clear departmental mission and vision, and to pivot the vision and team quickly in a rapidly shifting, growing environment.
• Track record operating a large, multi-site organization, including budget ownership, organizational design, and building engineering or platform functions.
• Commitment to building trust and fostering a culture that supports open communication and continuous improvement through feedback.
• Commitment to collaboration with gRED and pRED partners and leveraging CSCoE synergies.
• Ownership and a sharp focus on delivering results to the portfolio for the benefit of patients.
• High flexibility and ability to travel frequently internationally for this global role.

Responsibilities

• Define and execute an AI-driven drug discovery strategy, roadmap, and long-term vision, balancing technology development with portfolio impact.
• Set the strategy for Roche/Genentech’s Lab-in-the-Loop with partners across the REDs, supporting portfolio decision milestones, especially hit identification and lead optimization.
• Embed AI into discovery programs across gRED and pRED in partnership with therapeutic area and discovery leaders, and drive measurable portfolio impact.
• Integrate predictive computational methods, antibody design, protein engineering, and medicinal chemistry to support hypothesis-driven drug discovery.
• Monitor external advances, including co-folding and generative models, and decide where to build, adopt, or partner.
• Manage a balanced portfolio of AI investments, including portfolio-tied methods and frontier research, with appropriate resourcing, success criteria, and time horizons.
• Build and lead the global AIDD organization; hire, mentor, and set a high performance bar for AI/ML scientists, engineers, and managers.
• Set organizational strategy and make decisions about talent, infrastructure, resourcing, and capability development.
• Contribute to the strategic direction of computational research across Research and Early Development as a member of the CSCoE leadership team.
• Run AIDD as a global operation by owning budget and resource allocation across sites, designing an organization aligned with scientific strategy, and establishing a leadership operating rhythm.
• Drive sustained investment in engineering and platform capabilities supporting research and portfolio work.
• Establish AIDD as a central engine for generative AI, machine learning, and predictive modeling applied to structural biology, molecular design, and lead optimization.
• Build, scale, and deploy proprietary foundation models, deep learning architectures, and automated design loops in core discovery programs.
• Set the foundation model strategy, determining where proprietary models provide differentiation and where open models suffice, and build shared capabilities for portfolio programs and frontier research.
• Lead integration of autonomous agent systems, high-throughput active learning, and AI-driven workflows, while supporting continuous upskilling across discovery teams.
• Build a cohesive, high-performance culture based on trust, feedback, ownership, collaboration, and results delivery.
• Allocate global resources according to strategic priorities and identify, build, and sustain computational and data science capabilities by accessing premier talent pools.
• Own the strategy for hiring, developing, and retaining elite global talent.
• Foster open communication, collaboration, and continuous improvement through feedback.
• Partner with gRED and pRED and leverage synergies within the CSCoE, maintaining focus on portfolio results and patient benefit.

Benefits

• A discretionary annual bonus may be available based on individual and Company performance.
• The position qualifies for benefits detailed at the link provided in the posting.

What This Job Offers

• Job Type: Full-time
• Career Level: Executive
• Education Level: Ph.D. or professional degree