Machine Learning Engineer (Data and Digital Catalyst)
About The Position
The Machine Learning Engineer will join the Engineering - AI Enablement group within Roche’s Computational Sciences Center of Excellence and Data and Digital Catalyst organization. The group modernizes computational and data ecosystems and integrates digital technologies across Research and Early Development. It enables AI adoption, develops AI-based solutions to improve workflows, scales model training and inference, evaluates AI/ML models and outputs, and builds applications and technical utilities for scientific work. Working with computational and research scientists, AI/ML experts, product leaders, DevOps, and other partners, the engineer will build, own, and continually improve scalable AI/ML systems that make scientific data more useful and accelerate drug discovery and development. The role includes developing scientific web applications and backend systems, creating tools to assess model performance and quality, and contributing to data systems and engineering practices. The position is based at the South San Francisco campus, with onsite presence expected at least three days per week.
Requirements
- Strong proficiency with AI/ML frameworks, libraries, and toolsets.
- Expert knowledge of statistics, machine learning theory, and algorithms.
- Strong knowledge of ML performance optimization and GPU best practices.
- Experience with Kubernetes, relational databases, NoSQL databases, or data lakes.
- Experience working on cloud-native architectures in public clouds; AWS is preferred.
- Proven understanding and application of engineering best practices.
- Excellent communication skills and the ability to build trusted partnerships with internal and external collaborators.
- Ability to quickly acquire new technologies and programming languages, with a passion for continuous learning.
- Onsite presence at the South San Francisco campus at least three days per week.
Nice To Haves
- Experience with biological data, ideally multimodal, and scientific processes.
- Experience working with scientists or in a research environment.
- Experience with workflow automation, GenAI, and/or agents.
Responsibilities
- Design, develop, and test robust, scalable, and maintainable AI/ML-facing scientific web applications and backend systems.
- Build tools to evaluate AI/ML model performance and establish new ways to understand AI quality.
- Partner with product managers and scientists to understand user needs, shape requirements, and translate them into technical specifications.
- Develop and maintain systems for collecting, structuring, and storing diverse scientific data for advanced analytics, machine learning, and other data-driven initiatives.
- Implement, adopt, or evaluate AI/ML algorithms and analytical techniques.
- Contribute to architectural decisions, code reviews, and the evolution of development processes.
- Work across the technology stack and contribute beyond the engineer’s core area of expertise when needed.
- Stay up to date with emerging technologies and industry best practices, practicing continuous learning, collaboration, and curiosity.
Benefits
- A discretionary annual bonus may be available based on individual and Company performance.
- Relocation assistance benefits are not available for this posting.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
