Senior Machine Learning Engineer, AI Enablement

Position Overview

At Roche we advance science so that everyone has more time with the people they love. Our mission is to create a healthier future by innovating in drug discovery and development. Within our Computational Sciences Center of Excellence (CoE), the Engineering – AI Enablement group empowers our scientists by embedding AI into everyday work, driving impactful change in research and development.

As a machine learning engineer, you will build, own, and continually improve scalable AI/ML systems, working collaboratively with computational scientists, research scientists, product leaders, and DevOps teams to accelerate the discovery and development of life-changing treatments.

Key Responsibilities

• Design, develop, and test robust, scalable, and maintainable AI/ML scientific web applications and backend systems.
• Build tools to evaluate AI/ML model performance and establish new ways to measure AI quality.
• Partner with product managers and scientists to translate user needs into actionable technical specifications.
• Develop and maintain systems for collecting, structuring, and storing diverse scientific data that support advanced analytics and machine learning.
• Implement, adopt, or evaluate new AI/ML algorithms and analytical techniques.
• Contribute to architectural decisions, code reviews, and the evolution of our development processes.
• Be willing to work across the full stack, contributing beyond your core expertise as needed.
• Stay up-to-date with emerging technologies and best practices to foster a culture of continuous learning and collaboration.

Required Qualifications

• Bachelor's or Master’s in Computer Science (or similar technical field) with 4+ years of professional experience in machine learning engineering.
• Strong proficiency with AI/ML frameworks, libraries, and toolsets.
• Expert knowledge of statistics, machine learning theory, and algorithms.
• Solid understanding of ML performance optimization and GPU best practices.
• Experience with Kubernetes, relational databases, NoSQL databases, data lakes, and cloud-native architectures (ideally AWS).
• Proven application of engineering best practices and excellent communication skills.
• Ability to quickly acquire new technologies and a passion for continuous learning.

Preferred Qualifications

• Experience with imaging or biological data and processes.
• Prior work with scientists or in a research environment.
• Experience with workflow automation, GenAI, and/or agents.

Benefits & Perks

• Compensation: Expected salary range is $147,500–$273,900 (based on the primary location in California) with a discretionary annual bonus based on performance.
• Work Arrangement: This position requires onsite work 3 days per week.
• Relocation benefits are available.
• Qualifies for comprehensive benefits as detailed by the company.