The opportunity
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.
What you'll do
Design, build, evaluate, and ship LLM-based solutions that give users more: adaptive control over their listening experience
Work on prompted playlist experiences with a focus on music fulfillment and session generation
Collaborate with cross-functional partners across user research, design, data: science, product, and engineering
Prototype new ML approaches and bring them into production at global scale
Build and improve systems that connect artists and fans in personalized and meaningful ways
Contribute to the development of scalable ML systems serving hundreds of millions of users
What they're looking for
- You are experienced in machine learning and enjoy solving complex real-world: problems in collaborative environments
- You have a strong background in machine learning, natural language processing, and generative AI
- You are comfortable applying theory to build real-world, production-ready applications
- You have hands-on experience building and deploying end-to-end ML systems at scale
- You are familiar with LLM-based systems and techniques for improving them: using human feedback such as reinforcement fine-tuning, DPO, or similar approaches
- You have experience designing modular ML architectures and writing technical: specifications in partnership with product teams
- You are experienced with large-scale distributed data processing tools such as Apache Beam or Apache Spark
- You have worked with cloud platforms like GCP or AWS
