Machine Learning Engineer/Senior Machine Learning Engineer, Agentic Systems, AI for Drug Discovery
Confirmed on the employer's own hiring board on Oct 25, 2026. First seen by Alion on Sep 25, 2026.
A healthier future. It’s what drives us to innovate. To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come. Creating a world where we all have more time with the people we love. That’s what makes us Roche.
Advances in AI, data and computational sciences are transforming drug discovery and development. Roche’s Research and Early Development organizations at Genentech (gRED) and Pharma (pRED) have demonstrated how these technologies accelerate R&D, leveraging data and novel computational models to drive impact. Seamless data sharing and access to models across gRED and pRED are essential to maximising these opportunities. The Computational Sciences Center of Excellence (CS CoE) is a strategic, unified group whose goal is to harness the transformative power of data and Artificial Intelligence (AI) to assist our scientists in both pRED and gRED to deliver more innovative and life-changing medicines for patients worldwide.
The Opportunity
Within AI for Drug Discovery, the Software Engineering team builds and operates software platforms that put advanced models and computational tools into the hands of scientists. Our focus is on developing technology and deploying reliable, intuitive solutions that are adopted by users and create measurable impact across drug discovery. We are seeking a very talented Machine Learning Engineer to help build our agentic platform for molecule design. The platform enables scientists to use AI agents, computational models, scientific tools, and internal data sources together in coordinated workflows that support the design and evaluation of therapeutic molecules. In this role, you will develop production-quality software, integrate scientific and machine learning capabilities, and improve the experience of scientists using the platform. You will collaborate with software engineers, machine learning researchers, computational scientists, product managers, and drug discovery teams across Roche and Genentech.
In this role, you will:
- Develop and maintain backend services, APIs, and user-facing applications for an agentic drug design platform.
- Integrate machine learning models, scientific applications, databases, and internal services into reliable end-to-end workflows.
- Implement agentic capabilities, including tool execution, workflow orchestration, state management, evaluation, and observability.
- Build software that enables scientists to configure, run, inspect, and reproduce computational molecule design workflows.
- Deploy models and scientific tools into secure, scalable, cloud-based production environments.
- Write clean, maintainable, and well-tested code, and contribute to automated testing, documentation, code reviews, and CI/CD practices.
- Monitor deployed services, troubleshoot issues, and improve platform reliability, performance, and usability.
- Work closely with users to understand scientific needs, gather feedback, and translate requirements into practical software solutions.
- Contribute to technical design decisions and the ongoing evolution of the platform’s architecture.
- Develop familiarity with relevant drug discovery concepts and apply software engineering best practices in a scientific research environment.
Who You Are:
- For the Machine Learning Engineer level, you have a bachelor’s or master’s degree in Computer Science, Software Engineering, or a related technical field, or equivalent practical experience, and 3+ years of professional software engineering experience; and for the Senior Machine Learning Engineer level, you have a bachelor’s or master’s degree in Computer Science, Software Engineering, or a related technical field, or equivalent practical experience, and 5+ years of professional software engineering experience
- You are proficient in Python and have strong software engineering fundamentals, including API design, automated testing, data modeling, and system design.
- You have experience independently delivering production software from technical design and implementation through deployment, monitoring, and ongoing support.
- You have built backend services, platform capabilities, developer tools, or user-facing applications in a cloud environment.
- You are comfortable working with relational databases, asynchronous workflows, containers, version control, and CI/CD practices.
- You can translate user and scientific needs into practical technical solutions and communicate effectively with engineers, researchers, product managers, and domain experts.
- You are interested in AI-enabled applications and in integrating models, scientific tools, and data into reliable workflows.
- You are motivated by delivering software to users and improving real scientific workflows.
Preferred Qualifications:
- Experience with frontend development using a modern framework such as React.
- Familiarity with frameworks and standards for agentic applications, such as Model Context Protocol, workflow orchestration, retrieval systems, or evaluation frameworks.
- Experience developing software for scientific research, cheminformatics, computational chemistry, biology, or drug discovery.
Onsite presence, on our South San Francisco or NYC campus, is expected for at least 3 days a week.
Relocation benefits areNOT available for this job posting.
The expected salary range for this position based on the primary location of California for the Machine Learning Engineer is $147,600 -274,000, and for the Senior Machine Learning Engineer is $168,100 - 312,300. For the primary location of New York, the Machine Learning Engineer is $141,100 - 262,100, and the Senior Machine Learning Engineer is $160,900 - 298,700. 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. This position also qualifies for the benefits detailed at the link provided below.
#ComputationCoE
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