The Personalization team makes deciding what to play next easier and more enjoyable for every listener. From Blend to Discover Weekly, we’re behind some of Spotify’s most-loved features. We built them by understanding the world of music and podcasts better than anyone else. Join us and you’ll keep millions of users listening by making great recommendations to each and every one of them.
The Personalization (PZN) team is at the heart of how Spotify connects listeners with the content they love. Every day, hundreds of millions of people rely on the experiences we build, from Home and Search to Made For You and Discover Weekly.
Surfaces-NPV is an EU-based squad within the Surfaces Recommendations product area. We own recommendation quality on the Now Playing View, one of Spotify’s most personal and high-impact surfaces, and drive the introduction of new content verticals. We’re a small, senior-heavy team that values craft, autonomy, and shipping. We use AI coding tools such as Claude Code, experiment constantly, and believe the best ML engineers understand the full stack from user need to production system.
What You'll Do
Design, train, and ship machine learning models that power recommendations on the Now Playing View for hundreds of millions of users
Own ranking systems end-to-end, from experimentation and training pipelines to online serving and monitoring
Build and iterate on generative and agentic ML approaches to improve session steering and cross-content discovery
Work in an AI-native development environment, using AI tools to accelerate development while applying strong engineering judgment
Run A/B experiments, define success metrics, and translate improvements into measurable user impact
Collaborate closely with engineers, data scientists, researchers, and product managers to bring ideas into production
Shape the ML roadmap by identifying high-impact opportunities and mentor teammates
Who You Are
You have hands-on experience building recommendation or personalization systems at scale
You’re comfortable working across the ML stack, including pipelines, backend systems, and infrastructure
You think in products and understand how model decisions impact user experience
You’re fluent with AI-assisted development and use it to accelerate experimentation thoughtfully
You’re curious about emerging approaches like generative models and agentic ML systems
You’ve taken models from prototype to production and care about reliability and monitoring
You’re comfortable with ambiguity and enjoy defining new approaches in evolving problem spaces
Where You'll Be
This role is based in London
We offer you the flexibility to work where you work best! There will be some in person meetings, but still allows for flexibility to work from home.
