About this role
The Position
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
Genentech is seeking 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 AI 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 AI methods with real-world impact in the drug discovery field. The successful candidate will contribute to a research program focused on AI foundation models, including LLMs and agents, with the ultimate aim of accelerating the drug discovery process. They will work at the intersection of AI research and engineering challenges to build the next generation of biomedical large-scale foundation models. They will contribute to developing cutting-edge AI methods, including multimodal generative modeling, large language models, and reinforcement learning techniques. Furthermore, they will contribute to system design, scaling, and optimization across the full model-development lifecycle. The successful candidate will work in an exciting and multidisciplinary environment alongside AI scientists, ML engineers, and computational biologists.
In this role, you will:
• Drive research on novel foundation models, with a specific focus on multimodal generative models, LLMs, AI Agents, and reinforcement learning.
• Lead the design and implementation of novel, cutting-edge ML methods with applications to drug discovery and target discovery.
• Work at the intersection of deep learning and engineering challenges, focusing on system design, architectural choices, and scalability, in collaboration with the MLOps team.
• 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.
• Collaborate closely with interdisciplinary and cross-functional teams across gRED.
Who you are
• Educational Background: Ph.D. in Computer Science, Machine Learning, Statistics, Mathematics, Physics, or a related field.
• Excellent knowledge of the theory and practice of deep learning, as demonstrated in past projects and publication record at top-tier ML venues such as NeurIPS, ICML, ICLR, AISTATS, ACL, EMNLP, etc.
• Proven experience in developing and delivering innovative ML solutions, in particular in the following areas: large-scale representation learning, multi-modal generative modeling, reinforcement learning, large language modeling, AI agents.
• Excellent Python and PyTorch programming skills, with extensive knowledge of the best practices of software engineering, data engineering, and MLOps (e.g., familiar with code version control, high-performance compute infrastructures, and machine learning experiment monitoring workflows).
• Passionate about writing excellent software, system design, scaling, and optimization across the full model-development lifecycle.
• Excellent communication, collaboration, and problem-solving skills.
Relocation benefits are available for this job posting
The expected salary range for this position, based on the primary location of California, is $167,400 – 310,800. 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
#tech4lifeAI
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.
If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this form Accommodations for Applicants.
Company:
Genentech
Qualifications:
Language requirements:
Specific requirements:
Educational level:
Level of experience (years):
Senior (5+ years of experience)