Senior 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 both inside the team as well as throughout the organization
• Actively contribute to a strong community of machine learning practitioners at Spotify

Who You Are:

• 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 techniques 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:

• For this role, you can be within the North America region as long as we have a work location
• This team operates within the Eastern Standard time zone for collaboration

The United States base range for this position is $184,050 - $262,928 plus equity. The benefits available for this position include health insurance, six month paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, 13 paid flexible holidays, paid sick leave.