Senior Machine Learning Engineer - AI Enablement

About the role

Roche's Computational Sciences Center of Excellence (CoE) is building the infrastructure that turns AI into a reliable, high-impact utility for its researchers. Within the CoE, the AI Enablement Engineering group builds scalable systems, data pipelines and intelligent applications that help scientists work smarter. As a Senior Machine Learning Engineer, you will lead the architecture and delivery of systems that unlock scientific data across complex workstreams, owning end-to-end technical execution and setting architectural standards.

Key responsibilities

• Lead technical design, architecture and hands-on implementation of agentic AI solutions and scalable data pipelines.
• Drive end-to-end delivery of high-impact products and workstreams, establishing software engineering best practices (testing, CI/CD, documentation) and evaluation standards.
• Shape foundational architecture decisions, champion best practices through code reviews and resolve technical bottlenecks.
• Partner with computational scientists, product leaders and engineering teams to guide cross-functional teams and foster technical growth.
• Span the stack and contribute where needed, stay up to date with emerging technologies and share knowledge with colleagues.

Required profile

• Master's degree with 5+ years of professional experience, or a PhD with 3+ years in Computer Science or a related field, with a track record of complex workstreams and architectural best practices.
• Comfortable working across the ML lifecycle, from GPU optimization and model performance to backend systems and cloud-native architecture (e.g., Kubernetes, AWS).
• Solid knowledge of statistics and ML theory, and of AI/ML frameworks, libraries and toolsets.
• Experience with biological data (ideally multimodal) and processes is a strong plus; experience with scientists or in a research environment is advantageous.
• Experience with workflow automation, GenAI and/or agents is a plus.