Senior Machine Learning Engineer - Personalization
Spotify - New York, NY
Posted May 13, 2026
Benefits
- Parental leave
- Not verified
- Non-birth-parent leave
- Not verified
- Family-building benefits
-
- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
- Not verified
- Relocation assistance
- Not verified
- Childcare support
- Not verified
- Learning budget
- Not verified
- Verification
- Not verified
- Salary
- $210K-$260K From the posting source checked Jun 20, 2026
- 401(k) match
- Not verified
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Market context
- U.S. role benchmark (BLS OEWS)
- $116,543 U.S. median for this role
- Projected growth (BLS Employment Projections)
- +9.8% - Much faster than average
102% above the BLS role benchmark for software engineering aggregate.
Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.
Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.
Role
Schedule
- Shift type
- Not verified
- Weekend work
- Not verified
Company
Application
- Cover letter
- Not verified
- Assessment
- Not verified
- Deadline
- Not stated
Where they hire
State eligibility is not yet verified.
About this role
Senior Machine Learning Engineer - Personalization New York, NY The Personalization team makes deciding what to play next on Spotify easier and more enjoyable for every listener. We seek to understand the world of music better than anyone else so that we can make great recommendations to every individual and keep the world listening. Every day, hundreds of millions of people use the products we build, including destinations like Home and Search, original playlists like Discover Weekly and Daylist, and new innovations like AI DJ and AI Playlists. The Surfaces Music team is responsible for music recommendations across Spotify's most visible surfaces, including Home and the Now Playing experience. We own music shelf and candidate generation as well as the ranking models that power these experiences. Our models include embedding models for deep catalog discovery, new release recommendations, and a unified transformer-based generative personalization model that is poised to reshape how we deliver personalized experiences across Spotify. The Personalization team makes deciding what to play next on Spotify easier and more enjoyable for every listener. We seek to understand the world of music better than anyone else so that we can make great recommendations to every individual and keep the world listening. Every day, hundreds of millions of people use the products we build, including destinations like Home and Search, original playlists like Discover Weekly and Daylist, and new innovations like AI DJ and AI Playlists. The Surfaces Music team is responsible for music recommendations across Spotify's most visible surfaces,
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