Machine Learning Engineer - AI Enablement
AI in this role
At Roche you can show up as yourself, embraced for the unique qualities you bring. Our culture encourages personal expression, open dialogue, and genuine connections, where you are valued, accepted and respected for who you are, allowing you to thrive both personally and professionally. This is how we aim to prevent, stop and cure diseases and ensure everyone has access to healthcare today and for generations to come. Join Roche, where every voice matters.
The Position
As a Machine Learning Engineer, you will implement the infrastructure that unlocks our scientific data and accelerates the discovery of life-changing treatments. You will work at the intersection of computational engineering and biology, partnering with scientists, ML experts, and DevOps engineers to put powerful AI tools directly into the hands of those driving drug discovery.
This role is based in Welwyn, with onsite working three days per week.
The Opportunity:
You build tools to evaluate AI/ML model performance and establish new ways to understand and measure AI quality.
You partner with product managers and scientists to understand user needs, shape requirements, and translate them into actionable technical specifications.
You develop and maintain data systems for collecting, structuring, and storing diverse scientific data that power advanced analytics, machine learning, and other data-driven initiatives.
You implement, adopt, and evaluate new AI/ML algorithms and analytical techniques.
You own features end to end from initial model evaluation through to production deployment, within a team that prizes technical rigor and mentorship.
You shape how we build contributing to architectural decisions, code reviews, and the evolution of our development processes.
You span the stack and contribute where needed, staying curious about emerging technologies and industry best practices.
Who you are:
You bring technical rigor with a Bachelor's, Master's or PhD in Computer Science or a related technical field, and proven experience in machine learning engineering. You treat testing, clean code, and documentation as the foundation for scalable, high-impact systems.
You span the stack working across the ML lifecycle — from GPU optimization and model performance to backend systems and cloud-native architecture (e.g. Kubernetes, AWS) — with a solid grounding in statistics, ML theory, and modern AI/ML frameworks and tools.
You value collaborative engineering, seeing code reviews and architectural decisions as spaces for shared growth, and translating complex technical challenges into shared goals with partners from research scientists to DevOps engineers.
You are a continuous learner approaching new frameworks and languages with curiosity, as comfortable mentoring others as learning from them.
You are an excellent communicator translating technical complexity into clear, actionable insights with empathy and precision, so every stakeholder feels aligned and heard.
Preferred:
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.
If you want to build the tools that make AI an everyday utility for scientists — and help bring life-changing medicines to patients faster — apply now and join us.
Who we are
A healthier future drives us to innovate. Together, more than 100’000 employees across the globe are dedicated to advance science, ensuring everyone has access to healthcare today and for generations to come. Our efforts result in more than 26 million people treated with our medicines and over 30 billion tests conducted using our Diagnostics products. We empower each other to explore new possibilities, foster creativity, and keep our ambitions high, so we can deliver life-changing healthcare solutions that make a global impact.
Let’s build a healthier future, together.
The statements herein are intended to describe the general nature and level of work being performed by employees, and are not to be construed as an exhaustive list of responsibilities, duties, and skills required of personnel so classified. Furthermore, they do not establish a contract for employment and are subject to change at the discretion of Roche Products Ltd. At Roche Products we believe diversity drives innovation and we are committed to building a diverse and flexible working environment. All qualified applicants will receive consideration for employment without regard to race, religion or belief, sex, gender reassignment, sexual orientation, marriage and civil partnership, pregnancy and maternity, disability or age. We recognise the importance of flexible working and will review all applicants’ requests with care. At Roche difference is valued and we are proud to be an equal opportunity employer where you are encouraged to bring your whole self to work.
How we rate this
Machine Learning Engineer - AI Enablement at Roche rates 96 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- How do you decide that one model's output is better than another's for a given task?
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
Adapt your resume
- List these exact terms on your resume: AI Evaluation. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.
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