Staff Machine Learning Engineer, Home Surfaces

Spotify; United States; Sur place; USD 190 000 - 280 000; Plein temps

Résumé du poste

Spotify seeks a Staff Machine Learning Engineer to shape the future of personalized discovery and engagement. You’ll work at the intersection of recommendation systems, large language models, and production-scale machine learning infrastructure to build experiences that delight users.

This role is ideal for someone who thrives turning research into production, guiding technical direction in ambiguous spaces, and solving complex personalization challenges at global scale.

Responsabilités

• Help shape the future of personalized discovery and engagement at Spotify.
• Work at the intersection of recommendation systems, large language models, and production-scale ML infrastructure.
• Take models from research to production and drive technical direction in ambiguous problem spaces.

Description du poste

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.

Surfaces Moments is a ML team within the Personalization Mission focused on creating moment-based experiences across Spotify surfaces. The team owns and evolves the experiences that help listeners quickly connect with the content that matters most to them, including the Home Shortcuts experience and the underlying intelligence that powers it. By combining cutting-edge machine learning, recommendation systems, and product thinking, the team delivers highly relevant, personalized experiences to millions of listeners around the world.

As a Staff Machine Learning Engineer, you will help shape the future of personalized discovery and engagement at Spotify. You'll work at the intersection of recommendation systems, large language models, and production-scale machine learning infrastructure to build experiences that delight users and drive meaningful impact. This role is ideal for someone who enjoys taking models from research to production, driving technical direction in ambiguous problem spaces, and solving complex personalization challenges at global scale.