Internship: AI Infrastructure and MLOps Modernization through VibeOps (pRED)

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

Advances in AI, data, and computational sciences are transforming drug discovery. The new Computational Sciences Center of Excellence (CoE) unifies Genentech (gRED) and Pharma (pRED) efforts to leverage data and AI for innovative medicines. 

Within CoE, the Data and Digital Catalyst (DDC) modernizes computational and data ecosystems. The Engineering - AI Enablement group, within DDC, drives AI adoption, builds and deploys AI solutions to optimize workflows, scales model training and inference, and creates applications to accelerate drug discovery. They aim to make AI/ML an everyday utility for tasks from data analysis to documentation. 

The pRED-MLOps team within the AI Enablement group enables large-scale, reliable AI/ML solutions across the early development pipeline, providing a state-of-the-art platform for developing, deploying, and monitoring high-impact models to accelerate drug discovery. The team is cross-functional, impact driven, independent, and constantly evolving to meet the scientific needs.

The Opportunity

• VibeOps Research and Prototyping:  Research best practices, tools, and methodologies for applying VibeOps workflows in MLOps environments, with a focus on productivity, efficient cross-functional collaboration, and secure self-service, as well as an emphasis on understanding risks, limitations, and trade-offs

• Prototype small-scale solutions, focusing on VibeOps concepts and best practices, tools, and methodologies, within realistic MLOps contexts. The goal is experimentation, not production deployment. Additionally, develop benchmarks to validate the correctness of these prototypes. 

• Propose actionable steps for integrating "VibeOps" principles into our MLOps practices and tooling as future directions, to support secure, scalable self-service adoption over time.

• ML Platform Development: Assist in developing and documenting tools, pipelines, and frameworks that enhance the MLOps lifecycle (e.g., inference store integration, automated monitoring hooks, drift detection mechanisms) with an emphasis on self-service enablement for ML Engineers and Data Scientists. 

• AI Infrastructure Modernization: Contribute to the design, implementation, and optimization of modern infrastructure components (e.g., containerization, orchestration, distributed computing) to improve model training/inference speed, deployment reliability, and resource efficiency, specifically through a self-service lens. 

• Collaboration: Work closely with ML Engineers, Data Scientists, and IT infrastructure specialists, translating cutting-edge research into practical, scalable self-service solutions

Who You are

• You are an enrolled Master student or you have graduated as a Bachelor- or Master student within 12 months in Computer Science, Biotechnology or related field

• Experience in Python and experience with scripting/automation (e.g. Bash).

• Basic understanding of LLMs and Generative AI concepts, including prompts, context, limitations, and failure modes.

• Strong interest in Machine Learning Operations, DevOps principles.

• Strong problem-solving skills and a proactive, self-motivated approach to tackling complex challenges.

• Some experience with MLOps platforms/tools (e.g., MLflow, Kubeflow, SageMaker). 

• Some familiarity with CI/CD pipelines (e.g., GitLab CI, GitHub, Jenkins).

• Interest or exposure to Agentic AI concepts, such as tool calling, agent orchestration, or interoperability patterns (e.g., MCP). 

• Some foundational knowledge of cloud platforms (AWS, Azure, or GCP) and containerization technologies (e.g. Docker, Kubernetes). 

• Some understanding of distributed systems and parallel computing frameworks. 

Additional Information

• Location: Basel

• Duration: 6 months

• Preferred start date: 1st of July 2026

• Due to regulations non-EU/EFTA citizens must provide a certificate from the university stating that an internship is mandatory as part of the application documents

Ready to take the next step? We'd love to hear from you. Apply now to explore this exciting opportunity!

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.