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Home›Jobs›Spotify›Machine Learning Engineering Manager, Personalization
Spotify

About Spotify

The ultimate destination for music and podcasts

🏢 Tech, Media👥 1001+ employees📅 Founded 2006📍 Norrmalm, Stockholm, Stockholms län💰 $2.1b⭐ 4
B2CMusicEntertainmentDigital MediaSaaSMobile

Key Highlights

  • 180 million+ paying subscribers worldwide
  • $2.1 billion raised in Series G funding
  • Acquired Gimlet Media, Anchor, and Parcast for podcasting
  • Headquartered in Norrmalm, Stockholm with 1001+ employees

Spotify, headquartered in Norrmalm, Stockholm, is a leading commercial music streaming service with over 180 million paying subscribers globally. Founded to combat music piracy, Spotify has raised $2.1 billion in funding and is currently in its Series G stage. The platform not only offers a vast cat...

🎁 Benefits

Spotify offers global parental leave with six months of fully paid time off for new parents, flexible public holidays to align with personal values, a...

🌟 Culture

Spotify's culture is rooted in its mission to support creative artists while providing an accessible platform for fans. The company values innovation ...

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Spotify

Machine Learning Engineering Manager, Personalization

Spotify • New York, NY

Posted 1 month ago🏛️ On-SiteLeadMachine learning engineer📍 New york
Apply Now →

Skills & Technologies

Generative aiLarge language modelsMachine learning

Job Description

The Personalization team makes deciding what to play next easier and more enjoyable for every listener. From DJ 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 and by leveraging the latest in Generative AI. Join us and you’ll keep millions of users listening by giving great music and talk experiences to each and every one of them. We prefer that our team members be physically located in Eastern Standard/Daylight time zones for the purpose of our collaboration hours.

Personalization is looking for an ML Engineering Manager to help shape the future of how we give users more control of their experience, leveraging large language models (LLMs) and agentic workflows. This is an exciting mix of platform-level user understanding and experience level user presentation. 

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