Machine Learning Engineering Manager - Personalization

Spotify

New York, US

On-site

Who this role is best for

Best suited to mid-level machine learning engineers working in AI safety and personalization who thrive in cross-functional collaborations.

Best fit for

Engineers with experience in scalable AI systems for user recommendations.
— “build machine learning systems that help ensure Spotify experiences and recommendations”
Candidates who have worked on responsible AI and fairness in machine learning.
— “develop new approaches in areas like synthetic data, fairness, and responsible AI”
Professionals comfortable partnering with research and content teams.
— “partner closely with Tech Research, Trust & Safety, and Content Platform”

Things to consider

Focus on both current products and future AI-driven experiences.
— “support both today’s products and the next generation of AI-driven experiences”

How to stand out

Highlight past work on safety and responsibility in AI systems.
— “ensure Spotify experiences and recommendations are safe, responsible, and enjoyable”
Demonstrate experience with generative AI and recommendation systems.
— “newer generative AI experiences”
Showcase collaborations with research teams in machine learning projects.
— “partner closely with Tech Research”

Pace · Fast PacedCollaboration · HighAutonomy · MediumDecision Impact · TeamLevel · Manager

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

successful development and deployment of machine learning systems
positive user engagement and satisfaction

Typical background

experience in machine learning engineering

Skills & requirements

Required

Machine Learning EngineeringPersonalization SystemsAi-driven Product DevelopmentTeam Leadership

Preferred

Experience With Spotify's Music And Podcast Recommendation Systems

Stack & domain

Machine Learning SystemsSynthetic DataFairnessResponsible AiScalable SystemsHigh-impact SystemsPartnershipCollaborationInnovationResponsibilityEnjoymentMusicPodcastsRecommendationsAi-driven Experiences

About the role

Original posting from Spotify via Lever

Mission Statement
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.
About the Team
Safe-and-Sound is the centralized Safety team within the AI Foundations Studio in Personalization. We build machine learning systems that help ensure Spotify experiences and recommendations are safe, responsible, and enjoyable across core surfaces like Home, Search, as well as newer generative AI experiences.
We partner closely with Tech Research, Trust & Safety, and Content Platform to develop new approaches in areas like synthetic data, fairness, and responsible AI. Our focus is on building scalable, high-impact systems that support both today’s products and the next generation of AI-driven experiences.

Source: Spotify careers (Lever)