Research Scientist - Personalization

About this role

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. Spotify’s Personalization organization builds the technology that helps millions of listeners discover what they love. Within this space, our research team focuses on advancing the state of the art in machine learning and AI to shape the future of personalization. We explore new approaches, challenge existing assumptions, and contribute to the broader research community while influencing long-term product direction.

Conduct original research in machine learning and artificial intelligence, with a focus on large-scale foundation models and generative AI

Develop novel methodologies, models, and evaluation frameworks to advance personalization systems

Design and execute rigorous experiments to explore new ideas and validate research hypotheses

Contribute to the scientific community through publications, talks, and conference participation

Collaborate with cross-functional partners to translate research insights into long-term product opportunities

Help define and evolve a forward-looking research agenda aligned with Spotify’s personalization strategy

Mentor others and contribute to a strong, curious, and collaborative research culture You have a Master’s or PhD in machine learning, artificial intelligence, or a related field, or equivalent research experience

You have 2+ years of experience conducting research in machine learning or AI, ideally in an industry or academic setting

You have a track record of publications or contributions to top-tier conferences such as NeurIPS, ICML, ICLR, or similar

You have deep knowledge of machine learning, with experience in areas such as recommender systems, generative models, or representation learning

You are experienced in designing experiments and working with real-world datasets to validate research ideas

You care about advancing understanding of user behavior and improving experiences across music and talk content

You bring curiosity, creativity, and a thoughtful approach to solving complex, open-ended problems

You value collaboration and actively seek diverse perspectives in your work This role is based in New York City or Boston

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