Senior ML Scientist: Foundation Models for Drug Discovery

NLP PEOPLE; Daly City (CA); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Discretionary annual bonus

Job summary

Genentech is seeking a Senior ML Research Scientist to design and build foundation models for target and drug discovery, collaborating across gRED and Roche to accelerate translational science.

You will advance large-scale representation learning and multimodal models, integrate molecular, omics, and text data, and publish results at top conferences while fostering robust ML practices in an interdisciplinary team.

Qualifications

• PhD in Computer Science, ML, Computational Biology, or related field.
• 0–2+ years of industry or post-doc experience.
• Proven track record advancing ML models, especially in large-scale representation learning, multimodal generative models, LLMs, AI agents, and RL.
• Interest in AI for biology, chemistry, and drug discovery.
• Excellent knowledge of deep learning theory and practice.
• Proficient in Python; experienced with PyTorch or JAX.
• Strong software engineering, data engineering, and MLOps practices.

Responsibilities

• Design and build foundation models for target and drug discovery, focusing on large-scale representation learning, multimodal generative models, LLMs, AI agents, and RL.
• Integrate data modalities such as molecular structures, biological sequences, omics data, and text.
• Scale frontier AI models to massive datasets with emphasis on system design and MLOps collaboration.
• Publish in top ML venues and present results at conferences/workshops; collaborate with interdisciplinary teams across gRED and Roche.

Skills

Python programming

Deep learning theory

MLOps practices

Git/GitHub

PyTorch

JAX

Communication skills

Education

PhD in Computer Science / ML / Computational Biology

Tools

PyTorch

JAX

Git

MLflow

Job description

Genentech is seeking a Senior ML Research Scientist to design and build foundation models for target and drug discovery, collaborating across gRED and Roche to accelerate translational science.

You will advance large-scale representation learning and multimodal models, integrate molecular, omics, and text data, and publish results at top conferences while fostering robust ML practices in an interdisciplinary team.