Senior Machine Learning Engineer, Agentic Science & Generative Models

About the role

The AI Biology & Translation (AIBT) department of Genentech's Computational Sciences Center of Excellence is building AI systems for biology. It seeks a Senior ML Engineer for its Generative Modeling team to help build and scale foundation models and agentic systems for therapeutic discovery. The role covers agent design and orchestration, and the infrastructure, AgentOps and MLOps that make systems robust and scalable, depending on team coverage.

Key responsibilities

• Build agents that use tools, retrieve evidence and reason across multi-step scientific workflows
• Design interfaces between agents and biological, genomic and clinical data sources
• Design evaluation harnesses that check agent output against scientific ground truth
• Implement self-improving and autonomous loops for autoML and lab-in-the-loop
• Implement agent memory and context management for long-horizon workflows
• Build, fine-tune, deploy and scale foundation models and LLMs in production
• Own production Python/PyTorch (or JAX) codebases and the MLOps/AgentOps lifecycle (experiment tracking, evaluation, monitoring, CI/CD, IaC)
• Work with research scientists to turn open-ended problems into shippable systems

Required profile

• BS/MS in CS, ML, engineering or a related quantitative field
• 5+ years building and shipping ML systems in industry
• Track record leading technical projects end to end
• Interest or experience applying ML to scientific discovery (biology, chemistry, drug discovery)

Required skills

• Excellent Python; Git, automated testing, CI/CD, documentation
• Preferred: inference-time optimization, AWS infrastructure (EC2, S3, EKS, SageMaker), agent orchestration frameworks (LangGraph, MCP-based tool integration)

Salary range for the San Francisco location: $168,100 - $312,300; relocation benefits are not available.