Machine Learning Engineer (Data and Digital Catalyst)
About The Position
The Machine Learning Engineer will join the AI Enablement group within the Data and Digital Catalyst organization in Roche’s Computational Sciences Center of Excellence. The group supports the adoption of AI across Research and Early Development, builds and deploys AI-based solutions, scales model training and inference, evaluates model quality, and develops applications and technology foundations that help scientists advance drug discovery and development. Working with computational and research scientists, AI/ML experts, product leaders, DevOps, and other partners, the engineer will build, own, and continuously improve scalable AI/ML systems that make use of scientific data. The role is based at the South San Francisco campus, with onsite presence expected at least three days per week. The position is open at SE5 and SE6 levels, with final leveling determined during the interview process.
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 ability to build trusted partnerships with internal and external collaborators.
- Ability to quickly acquire new technologies and programming languages, and a passion for continuous learning.
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.
- Experience with AWS.
Responsibilities
- Design, develop, and test robust, scalable, maintainable AI/ML-facing scientific web applications and backend systems.
- Build tools to evaluate AI/ML model performance and develop 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 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 improvements to development processes.
- Contribute across the technology stack as needed, including outside the engineer’s core area of expertise.
- Keep current with emerging technologies and industry best practices, and foster continuous learning, collaboration, and curiosity.
Benefits
- A discretionary annual bonus may be available based on individual and Company performance.
- Relocation assistance is not available for this posting.
- The posting references benefits detailed under a Benefits heading but does not list specific benefits.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
