About this Senior Principal Machine Learning Scientist, AI Biology & Translation (AIBT) role at Roche
A healthier future. It’s what drives us to innovate. To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come. Creating a world where we all have more time with the people we love. That’s what makes us Roche.
Advances in AI, data, and computational sciences are transforming drug discovery and development. Roche’s Research and Early Development organisations at Genentech (gRED) and Pharma (pRED) have demonstrated how these technologies accelerate R&D, leveraging data and novel computational models to drive impact. Seamless data sharing and access to models across gRED and pRED are essential to maximising these opportunities. The new Computational Sciences Center of Excellence (CoE) is a strategic, unified group whose goal is to harness this transformative power of data and Artificial Intelligence (AI) to assist our scientists in both pRED and gRED to deliver more innovative and transformative medicines for patients worldwide.
The Opportunity
The AI Biology & Translation (AIBT) department within Genentech's Computational Sciences Center of Excellence (CS-CoE) is building the next generation of AI systems for biology. Our mission is to develop AI models that learn from biological data at unprecedented scale, generating new insights into disease mechanisms, therapeutic opportunities, and human biology.
We are seeking an exceptional scientist to lead a research program focused on Genomics AI and Biological Foundation Models. This role is ideal for a researcher with a strong track record in machine learning, sequence modeling, regulatory genomics, and representation learning who is excited about advancing the frontier of AI for biology.
As a Senior Principal Scientist, you will lead a team developing AI models that learn from genomic sequence, gene regulation, cellular state, perturbational biology, and multimodal biological data. You will help define Genentech's strategy for applying modern machine learning to biological discovery and establish new capabilities that accelerate therapeutic innovation across the R&D portfolio.
Key Responsibilities:
Lead Genomics AI Strategy: Define the scientific roadmap and strategy for genomics foundation models to accelerate therapeutic innovation across Genentech’s portfolio.
Advance AI Methodology: Develop state-of-the-art sequence modeling, self-supervised learning, and generative models using multimodal biological data (genomics, chromatin state, cellular context).
Drive Biological Discovery: Partner with experimental groups to translate machine learning innovation into insights for target discovery and disease understanding.
Influence Organizational Direction: Serve as a scientific leader within AIBT to shape Genentech's long-term AI-for-biology strategy.
Publish & Present: Maintain scientific excellence by publishing in top-tier ML/genomics venues and representing Genentech at global conferences.
Evaluate Emerging Tech: Assess cutting-edge advancements in machine learning to identify new opportunities for transformative scientific impact.
Mentor Teams: Lead and mentor a team of scientists, fostering a culture of innovation, excellence, and collaboration.
Who you are
Required:
Education: PhD in Computer Science, Machine Learning, Computational Biology, Physics, or a related quantitative field.
Experience: Minimum 7 years of post-PhD research experience developing innovative AI/ML methods to advance biological discovery.
Technical Expertise: Deep knowledge of foundation models, sequence modeling, self-supervised learning, generative AI, or multimodal ML, and expertise in gene regulation, epigenomics, functional genomics, regulatory biology, or cellular systems biology
Publication Track Record: Strong history of publishing novel computational methods in leading AI, machine learning, or genomics venues.
Leadership: Proven ability to lead complex scientific initiatives and influence across multiple disciplines.
Field Impact: Recognition via influential publications, open-source software, invited presentations, or patents that have shaped the field.
Relocation benefits are available for this job posting.
The expected salary range for this position based on the primary location of South San Francisco, CA is $202,800 - $376,600. Actual pay will be determined based 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. This position also qualifies for the benefits detailed at the link provided below.
#ComputationCoE
#tech4lifeComputationalScience
Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws.
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