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 the 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

We seek a highly motivated Senior/Principal AI Scientist to join the Foundation Models team (DELTA) within the AIBT (AI for Biology & Translation) department in Genentech Research and Early Development (gRED). Our team drives cutting-edge AI research that delivers real-world impact in drug and target discovery, with a focus on large-scale foundation models in biology. Our ambition is to build models that reason across biological modalities, guide experiments, and learn from their outcomes to accelerate scientific discovery.

The successful candidate will help shape and develop the next generation of large-scale foundation models, with the ultimate aim of accelerating target and drug discovery. In this role, the candidate will advance AI research in multimodal generative modeling, representation learning, LLM mid-training and post-training, agentic science, and reinforcement learning, with direct applications to genomics, perturbation biology, imaging, and multimodal experimental data.

The candidate will join an exciting, multidisciplinary research environment alongside AI scientists, AI engineers, and computational biologists. This role requires a deep, demonstrated background in deep learning and a strong passion for advancing the frontier of AI in science. The selected candidate will be a technical and scientific leader, shaping research directions, developing and testing new ideas, and tackling the modeling, data, and engineering challenges needed to make them work at scale. They are expected to lead high-profile collaborative projects and to routinely publish in top-tier machine learning and scientific venues.

In this role, you will:

• Design and build foundation models to support target and drug discovery, with a focus on large-scale representation learning, multimodal mid-training and post-training, reasoning, and reinforcement learning.
• Develop scalable approaches to curate, organize, and integrate diverse data modalities such as molecular structures, biological sequences, omics data, biochemical readouts, and text into high-quality training data and evaluation tasks.
• Develop models and agentic systems that propose experiments, interpret results, and learn from experimental feedback, advancing lab-in-the-loop discovery.
• Build training and evaluation environments from biological data to develop and measure scientific reasoning and discovery capabilities.
• Scale state-of-the-art models to massive datasets, working at the intersection of deep learning and engineering, from distributed training and efficient experimentation to reliable data pipelines, in collaboration with engineering and MLOps teams.
• Publish in top-tier ML venues and scientific journals, and present results at internal and external conferences and workshops.

For the Principal AI Scientist level:

• Define and drive larger research initiatives within these areas, turning open scientific challenges into coherent research agendas and delivering advances from initial ideas through rigorous evaluation and scientific impact.
• Set technical direction across related projects and resolve critical modeling, data, and engineering challenges while remaining deeply involved in hands-on research and development.

Who you are:

• Educational background: Ph.D. in Computer Science, Machine Learning, Computational Biology, or a related quantitative field.
  
  
• Experience:
  • Proven track record advancing AI models in research and/or industry settings, with deep expertise in one or more of large-scale representation learning, multimodal generative models, LLMs, AI agents, or reinforcement learning.
  • Strong motivation to push the frontier of AI for science and translate advances in AI into meaningful progress in biology and drug discovery.
  • Prior experience applying AI to biology, chemistry, or drug discovery is a plus, especially with multimodal experimental data or experimental design.
    
• Technical skills:
  • Excellent knowledge of the theory and practice of deep learning, with strong research intuition and the ability to turn open scientific questions into rigorous experiments.
  • Proven experience developing and delivering innovative ML solutions in the areas above.
  • Excellent Python programming skills, fluency with modern agentic coding environments, and extensive experience with AI frameworks such as PyTorch or JAX.
  • Strong grasp of software engineering, data engineering, and MLOps best practices, including scalable data processing, high-performance computing, and reproducible training and evaluation workflows.
  • Strong publication record and active contribution to research communities, including top-tier ML venues such as NeurIPS, ICML, and ICLR, and/or a public portfolio demonstrating substantial contributions to relevant AI projects.
  • Excellent communication, collaboration, and problem-solving skills.
    
• Preferred
  • Practical experience bridging innovative ML methods and applications in target/drug discovery.
  • Experience with biological and chemical modalities and tasks such as molecular structures, single-cell/omics data, perturbation biology, and multimodal biological datasets.
  • Hands-on experience developing, finetuning, and optimizing LLMs and agentic systems.

For the Principal AI Scientist level:

• Typically 3+ years of post-Ph.D. research experience in relevant AI areas, or an equivalent portfolio of research contributions demonstrating comparable depth, independence, and impact.
• A strong track record of driving complex research initiatives with substantial scientific or technical impact, demonstrating the judgment to identify high-value problems and make consequential technical decisions.

Relocation benefits are NOT available for this job posting

The expected salary range for this position, based on the primary location of San Francisco, is $168,100 - 312,300 for the Senior AI Scientist and $201,300 - 373,800. 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.

Benefits

#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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