Bachelor’s degree with 5+ years or Master’s degree with 3+ years in Computer Science, Machine Learning, Software Engineering, or equivalent experience.
Strong proficiency in AI/ML frameworks and statistical modeling.
Hands-on experience with cloud-native architectures, preferably AWS, and Kubernetes.
Familiarity with relational, NoSQL, or data lake storage systems.
Ability to communicate effectively and build collaborative partnerships across teams.
Responsibilities
Design, develop, and test scalable scientific web applications and backend systems.
Build foundational AgentOps capabilities for deploying AI agents at scale.
Establish AI data readiness by structuring and validating scientific datasets.
Develop tooling to evaluate AI/ML model performance and define new quality metrics.
Partner with product managers and scientists to translate scientific challenges into technical specifications.
Implement and evaluate emerging AI/ML algorithms and GPU performance optimizations.
Benefits
Hybrid work schedule with 3 days on campus in South San Francisco.
Opportunity to work in a cross-functional, impact-driven team.
Engagement with cutting-edge AI/ML technologies in drug discovery.
Collaboration with computational and research scientists.
Full Job Description
The Opportunity
Join our Data and Digital Catalyst organization as a Senior AI Engineer in AI Enablement, where you will partner closely with computational and research scientists to turn artificial intelligence into an everyday utility that accelerates drug discovery and development. Working in a cross-functional, impact-driven team, you will design, build, and scale modern AI/ML and agentic systems that unlock the full potential of our scientific data.
Design, develop, and test robust, scalable scientific web applications, backend systems, and cloud-native architectures that power AI/ML workflows.
Build foundational AgentOps capabilities—including evaluation frameworks, observability, secure execution environments, memory/retrieval systems, and model routing—to deploy and operate AI agents at scale.
Establish AI data readiness capabilities by structuring, validating, and standardizing diverse scientific datasets to ensure reproducibility, traceability, and trustworthiness.
Develop tooling to evaluate AI/ML model performance and define new metrics for assessing AI output quality.
Partner directly with product managers, computational scientists, and research teams to translate complex scientific challenges into actionable technical specifications.
Implement and evaluate emerging AI/ML algorithms, analytical techniques, and GPU performance optimizations to continuously evolve our modern tech stack.
Who you are:
You hold a Bachelor’s degree with 5+ years of relevant experience (or a Master’s degree with 3+ years) in Computer Science, Machine Learning, Software Engineering, or an equivalent practical background.
You bring strong proficiency in AI/ML frameworks, statistical modeling, machine learning theory, and GPU/ML performance optimization.
You have hands-on experience building cloud-native architectures (ideally AWS) using Kubernetes alongside relational, NoSQL, or data lake storage systems.
You apply software engineering best practices across the full stack and demonstrate agility in quickly picking up new technologies and languages.
You communicate clearly and excel at building trusted, collaborative partnerships across technical and non-technical teams.
Preferred
Experience working with biological data, scientific imaging, or within a life sciences research environment.
Hands-on experience building and deploying Generative AI solutions, autonomous agents, or workflow automation tools.
Location
This role is based in South San Francisco and offers a hybrid schedule working 3 day per week on campus
No relocation benefits are available for this posting
The expected salary range for this position based on the primary location of San Franscico, CA is $168,100- $312,300 Annual. This position is open to both SE6 and SE7 levels, with final leveling to be determined upon completion of the interview process. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance.
About Roche
Roche Holding AG is a Swiss multinational healthcare company that operates worldwide under two divisions: Pharmaceuticals and Diagnostics. Its holding company, Roche Holding AG, has bearer shares listed on the SIX Swiss Exchange. The company headquarters are located in Basel. Roche is the largest pharmaceutical company in the world, and the leading provider of cancer treatments globally. The company also produces a range of diagnostic tests for medical professionals and patients. Roche was one of the first companies to bring targeted treatments to patients. In 2019, Roche had over 100,000 employees worldwide, and generated revenue of CHF 61.5 billion.
