Senior Machine Learning Scientist, Foundational ML, AI for Biology & Translation (AIBT)

Opportunity We seek a highly motivated Senior ML 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. Responsibilities Design and build foundation models to support target and drug discovery, focusing on large‑scale representation learning, multimodal generative models, LLMs, AI agents, and reinforcement learning. Work with and integrate diverse data modalities such as molecular structures, biological sequences, omics data, biochemical readouts, and text. Bridge cutting‑edge AI models and applications supporting target discovery, experimental design, and lab‑in‑the‑loop pipelines. Scale frontier AI models to massive datasets, focusing on system design, architectural choices, and scalability, 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. Collaborate closely with interdisciplinary and cross‑functional teams across gRED and Roche. Qualifications Ph.D. in Computer Science, Machine Learning, Computational Biology, or a related quantitative field. 0–2+ years of industry or post‑doc experience. Proven track record advancing ML models in research and/or industry settings, particularly in large‑scale representation learning, multimodal generative models, LLMs, AI agents, and reinforcement learning. Demonstrated interest in advancing AI for scientific applications spanning biology, chemistry, and drug discovery. Excellent knowledge of the theory and practice of deep learning. Proven experience developing and delivering innovative ML solutions. Excellent Python programming skills, fluency with modern agentic coding environments, and extensive experience with ML frameworks such as PyTorch or JAX. Strong grasp of software engineering, data engineering, and MLOps best practices (e.g., version control, high‑performance compute infrastructures, and ML experiment monitoring workflows). Strong publication record and active contribution to research communities, including top‑tier ML venues such as NeurIPS, ICML, ICLR, AAAI, ACL, EMNLP, AISTATS, etc. and/or public portfolio of relevant projects. Excellent communication, collaboration, and problem‑solving skills. Preferred Qualifications 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, fine‑tuning, and optimizing LLMs and agentic systems. Relocation benefits are NOT available for this job posting. Salary range: $147,800 – $274,400 (San Francisco). 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. 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 the Accommodations for Applicants form. #J-18808-Ljbffr F. Hoffmann-La Roche AG