Machine Learning Engineer - Personalization, Horizon

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. You’ll join the Horizon Product Area within the Sessions Studio, part of Spotify’s Personalization Mission. This team focuses on inventing and evolving new listening experiences powered by emerging technologies.

From AI DJ to promptable playlists and generated podcasts, we’re exploring how agentic systems and generative AI can reshape how people interact with audio. You’ll work at the intersection of product innovation and cutting-edge machine learning to bring entirely new experiences to life for millions of listeners. What You'll Do Design, build, evaluate, and ship agentic based features and interactive experiences to bring our products to the next level Collaborate with cross functional teams spanning user research, design, data science, product management, and engineering to build new product features that advance our mission to connect artists and fans in personalized and useful ways Prototype new approaches and productionize solutions at scale for our hundreds of millions of active users Promote and role-model best practices of ML systems development, testing, evaluation, etc., both inside the team as well as throughout the organization Actively contributed to a strong community of machine learning practitioners at Spotify Who You Are An experienced ML practitioner motivated to work on complex real-world problems in a fast-paced and collaborative environment Strong background in machine learning, natural language processing, and generative AI, with experience in applying theory to develop real-world applications Hands-on expertise with implementing end-to-end production ML systems at scale.

Experience with production LLM scale based systems is a plus Experience with incorporating human feedback to improve LLM based systems using technicals like DPO, KTO, and reinforcement fine-tuning Experience with designing end-to-end tech specs and modular architectures for ML frameworks in complex problem spaces in collaboration with product teams Experience with large scale, distributed data processing frameworks/tools like Apache Beam, Apache Spark, and cloud platforms like GCP or AWS Where You'll Be We offer you the flexibility to work where you work best! For this role, you can be within the European region as long as we have a work location. This team operates within the GMT/CET time zone for collaboration.

Excluding France due to on-call restrictions.