Machine Learning Engineer (AI Enablement)
About The Position
The Machine Learning Engineer will join Roche’s Engineering - AI Enablement group within the Data and Digital Catalyst organisation, part of the Computational Sciences Center of Excellence. The group enables 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 support drug discovery and development. The role works closely with computational and research scientists, AI/ML experts, product leaders, DevOps, and other collaborators. The engineer will build, own, and continuously improve scalable AI/ML systems that make scientific data useful and accelerate discovery and development of treatments. Onsite presence at the South San Francisco campus is expected at least three days per week. Relocation assistance is not available. The position is open to SE5 and SE6 levels, with final leveling determined after interviews. A discretionary annual bonus may be available based on individual and company performance.
Requirements
- Bachelor’s degree.
- 1–3 years of experience 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, 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 actionable technical specifications.
- Develop and maintain systems for collecting, structuring, and storing diverse scientific data that support advanced analytics, machine learning, and other data-driven initiatives.
- Implement, adopt, or evaluate new AI/ML algorithms and analytical techniques.
- Contribute to architectural decisions, code reviews, and the evolution of development processes.
- Span the technology stack and contribute where needed, including outside the engineer’s core area of expertise.
- Keep up to date with emerging technologies and industry best practices, and contribute to a culture of continuous learning, collaboration, and curiosity.
Benefits
- A discretionary annual bonus may be available based on individual and company performance.
- The position qualifies for the benefits detailed in the Benefits section; specific benefits are not listed in the posting.
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
