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About the Role
Roche's AI for Drug Discovery (AIDD) group (Prescient Design) is revolutionizing drug discovery with cutting-edge machine learning. We are seeking a Principal Machine Learning Engineer to join our Foundation Models team. In this role, you will drive the engineering, scaling, and operationalization of our internal reasoning Large Language Models (LLMs) and agentic systems, enabling them to succeed at complex biomolecular design and autonomous scientific workflows. You will work at the intersection of engineering and research, spanning the full stack: from the agent orchestration logic that makes these systems scientifically useful, to the distributed infrastructure and MLOps/AgentOps that make them robust at scale.
Responsibilities
- Architect and deploy autonomous agents that utilize tools, retrieve scientific evidence, and execute multi-step reasoning across drug discovery workflows.
- Design and implement advanced agent memory architectures and context management for long-horizon scientific tasks.
- Build reliable interfaces between agents and genomic, chemical, and clinical data sources.
- Design, build, and optimize large-scale distributed training and inference systems for foundation models.
- Own the production Python/PyTorch codebases that turn fast-moving research into enterprise-grade software.
- Establish best practices for the full lifecycle: experiment tracking, system observability and monitoring, rigorous evaluation harnesses, CI/CD, and infrastructure.
- Define the long-term engineering roadmap for AI4DD’s agentic and foundation models.
- Serve as a technical authority on ML infra for Genentech leadership, architect cross-functional platforms, and elevate the engineering bar across gRED.
- Partner closely with ML Scientists and domain experts to translate open-ended scientific problems and complex reasoning objectives into scoped, shippable, and highly efficient systems.
Requirements
- BS, MS, or PhD in Computer Science, Machine Learning, Engineering, or a related quantitative field.
- Demonstrated track record of technical leadership with increasing levels of experience based on degree: PhD with 5+ years, MS with 8+ years, or BS with 10+ years of industry experience building, shipping, and owning large-scale ML systems and infrastructure end-to-end.
- Exceptional Python programming skills and rigorous software engineering fundamentals (Git, automated testing, CI/CD, documentation, architecture design).
- Extensive hands-on experience with modern deep learning frameworks (PyTorch, JAX) and deploying ML infrastructure on AWS or HPC environments, including distributed training tools.
- Practical experience designing agent orchestration frameworks (e.g., LangGraph, MCP-based tool integration), managing persistent agent memory, and building self-improving loops.
- Strong passion for applying frontier AI and agentic science to AI for Drug Discovery (AI4DD), biology, and chemistry.
- Deep expertise in LLM serving, test-time compute, sampling/search strategies, model routing, batching, caching, and latency/cost/quality tradeoffs.
- Experience working with molecular modalities (e.g., protein sequences, chemical graphs, and structured molecular data).
- A public portfolio of significant technical contributions to open-source ML, systems, or MLOps libraries.
Skills
- Python
- PyTorch
- JAX
- AWS
- HPC
- Git
- CI/CD
- MLOps
- AgentOps
- Large Language Models (LLMs)
- Agent orchestration frameworks
- Deep learning
- Distributed systems
Location
- New York
Work Type
- Onsite
Experience Level
- Principal
Education Level
- BS
- MS
- PhD
Salary/Compensations
- $192,500 - $357,500
Benefits
- Discretionary annual bonus
- Detailed benefits available at provided link
About the Company
- Roche's Research and Early Development organizations at Genentech (gRED) and Pharma (pRED) are leveraging AI, data, and computational sciences to transform drug discovery and development.
- The new Computational Sciences Center of Excellence (CoE) is a strategic, unified group aiming to harness the power of data and Artificial Intelligence (AI) to assist scientists in delivering innovative medicines.
- Genentech is committed to advancing science and ensuring access to healthcare for current and future generations.
Equal Opportunity
- 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.