Senior Engineer - Machine Learning & AI Enablement
Roche is hiring a Senior Engineer - Machine Learning & AI Enablement in Basel, Switzerland. Level rates it ; you can apply on Level.
AI in this role
Build scalable systems, data pipelines, and AI enablement infrastructure to accelerate drug discovery at Roche.
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
At Roche, we advance science so that we all have more time with the people we love. A healthier future. For a world where everyone has access to the healthcare they need today and for the generations to come. For this, we believe the next breakthrough in medicine will be powered by the intersection of computational engineering and biology. We are building the infrastructure that transforms AI from an experimental concept into a reliable, high-impact utility for our researchers.
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. The new Computational Sciences Center of Excellence (CoE) is a strategic, unified group whose goal is to harness this transformative power of data and AI to assist scientists to deliver more innovative and transformative medicines for patients worldwide.
Within the CoE, the Data and Digital Catalyst (DDC) organisation drives the modernization of computational and data ecosystems and integration of digital technologies across Research & Early Development. The AI Enablement Engineering group sits at the heart of this mission. We aren't just training models; we are building scalable systems, data pipelines, and intelligent applications that enable our scientists to work smarter, not harder. From optimizing model performance to designing end-to-end agentic workflows, our goal is to put powerful AI tools directly into the hands of those driving drug discovery to power data-driven science and accelerate decision making.
We are a cross-functional, impact-driven team that values cognitive diversity and technical excellence. Here, you’ll partner with biologists, computational scientists, data experts, and researchers to architect a future where AI/ML is an essential component of every scientific discovery. If you’re an engineer who thrives on solving complex problems, spans the stack with curiosity, and wants to build tools that truly change lives, we want to hear from you.
The Opportunity
As a Senior Machine Learning Engineer in AI Enablement, you will lead the architecture and delivery of systems that unlock scientific data across complex workstreams. You will own end-to-end technical execution, setting architectural standards that turn AI into a reliable, high-impact utility for researchers.
Partnering across computational sciences, product leaders, and engineering teams, you will drive technical strategy and take ownership of critical AI/ML products. You will combine engineering rigor with proactive problem solving to guide cross-functional teams and foster technical growth across the organization.
- Lead technical design, architecture, and hands-on implementation of agentic AI solutions and scalable data pipelines to solve complex scientific challenges.
- 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 proactively resolve technical bottlenecks.
- Be willing to span the stack and contribute where needed, even outside of your core area of expertise.
- Stay up-to-date with emerging technologies and industry best practices and adopt a culture of continuous learning, collaboration, and curiosity.
Who You Are
- You lead with technical rigor and ownership: You hold a 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 driving complex workstreams and establishing architectural best practices.
- You span the stack: You are comfortable working across the ML lifecycle, from GPU optimization and model performance to backend systems and cloud-native architecture (e.g., Kubernetes, AWS) with solid knowledge of statistics and ML theory as well as AI/ML frameworks, libraries, and toolsets
- You own project delivery and architecture: You excel at delivering AI/ML products, proactively identifying risks, and guiding cross-functional teams (from researchers to DevOps engineers) toward robust, maintainable solutions.
- You are a continuous learner: You approach new frameworks and languages with curiosity. You are as comfortable mentoring others as you are learning from them, and you actively contribute to a culture of collective growth.
- You are an excellent communicator: You excel at translating technical complexity into clear, actionable insights for diverse audiences. You communicate with empathy and precision, ensuring that technical trade-offs are well-understood and that all stakeholders, from research scientists to engineers, feel aligned and heard.
- Experience with biological data (ideally multimodal) and processes is a strong plus.
- Experience working with scientists or in a research environment is advantageous.
- Experience with workflow automation, GenAI, and/or agents is a plus.
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.
Roche is an Equal Opportunity Employer.
How we rate this
Senior Engineer - Machine Learning & AI Enablement at Roche rates 90 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
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- How do you decide when an AI agent can act on its own versus asking for approval first?
- Tell me about a project where machine learning was part of your work. What did you do?
- Tell me about a project where ai enablement was part of your work. What did you do?
- Tell me about a project where mlops was part of your work. What did you do?
- Tell me about a project where data pipelines was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: AI agents, Machine learning, AI Enablement, MLOps, and Data Pipelines. 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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