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28 d agofound 6 h ago

Staff Machine Learning Engineer, Home Surfaces

Spotify·New York, NY·via Lever

Posted by Spotify on 21 September 2026, 28 days ago. Still on their Lever board when we checked 19 min ago. Half of Spotify's roles come down within 39 days.

remotestaff5+ yrsFull timellmml
What the posting is about

Shape personalized discovery and engagement for millions of users. Work on recommendation systems and large language models. Take models from research to production.

Read out of the posting
Levelstaff
Experience asked5+ years
EmploymentFull time
LocationNew York, NY
RemoteYes
Visa sponsorshipNot stated
SalaryNot published, and most postings do not
Posted2026-09-21
Found vialever, direct from their system

We saw it 28 days after it went up.

The posting, as the company wrote it
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. The Surfaces Podcasts team owns podcast recommendations across some of Spotify’s most visible surfaces, including Home and the Now Playing view. We build and improve the recommendation systems that help listeners discover their next favorite show or episode while helping creators reach the right audiences. As a Staff Machine Learning Engineer, you’ll 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 for listeners at global scale. You’ll take models from research to production, help set technical direction in ambiguous problem spaces, and solve complex personalization challenges across Spotify.

Copied from Spotify’s own board, not rewritten. Original ↗

Also open at Spotify

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