1 month ago
Base Salary
$193k - $358k/yr
Responsibilities
- Architect and deploy autonomous agents that use tools, retrieve scientific evidence, and execute multi-step reasoning across drug discovery workflows.
- Design agent memory architectures, context management systems, and interfaces to genomic, chemical, and clinical data sources.
- Design, build, and optimize distributed training and inference systems for foundation models.
- Own production Python and PyTorch codebases and translate research systems into enterprise-grade software.
- Establish MLOps/AgentOps practices covering experiment tracking, observability, monitoring, evaluation harnesses, CI/CD, and infrastructure.
- Define the engineering roadmap for agentic and foundation models, advise Genentech leadership, and architect cross-functional platforms.
- Partner with ML scientists and domain experts to convert scientific problems into efficient, shippable systems.
Requirements
- BS, MS, or PhD in Computer Science, Machine Learning, Engineering, or a related quantitative field, with 5+ years for a PhD, 8+ years for an MS, or 10+ years for a BS.
- Demonstrated technical leadership and experience building, shipping, and owning large-scale ML systems and infrastructure end to end.
- Exceptional Python programming skills and strong software engineering fundamentals, including Git, automated testing, CI/CD, documentation, and architecture design.
- Extensive hands-on experience with PyTorch or JAX and deploying ML infrastructure on AWS or HPC environments, including distributed training tools.
- Practical experience designing agent orchestration frameworks such as LangGraph or MCP-based tool integrations, managing persistent agent memory, and building self-improving loops.
- Deep expertise in LLM serving, test-time compute, sampling and search strategies, model routing, batching, caching, and latency, cost, and quality tradeoffs.
- Experience with molecular modalities such as protein sequences, chemical graphs, and structured molecular data is preferred.
- A public portfolio of significant contributions to open-source ML, systems, or MLOps libraries is preferred.
- Strong interest in applying frontier AI and agentic science to drug discovery, biology, and chemistry.
Benefits
- Onsite presence at the Roche/Genentech campus is expected under company policy.
- Relocation benefits are not available for this posting.
- The position qualifies for the company benefits described in the linked benefits information.
- A discretionary annual bonus may be available based on individual and company performance.
Categories
About Genentech
Genentech discovers, develops, and commercializes biologic therapies for serious diseases across oncology, immunology, neuroscience, ophthalmology, infectious disease, and metabolism. Founded in 1976 and headquartered in South San Francisco, it operates as a member of the Roche Group, with research centered in its gRED organization and revenue driven by prescription drug sales and collaborations.