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Senior Applied Research Scientist - PersonalizationSpotify · London
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Spotify

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Senior Applied Research Scientist - Personalization

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🗓️ Posted 2026-09-21 London Permanent Hybrid ICT
💰 Salary Not shared 📊 Market 7,000 GBP–10,833 GBP/mo

About the Company

Passionate music fans. Innovative tech pros. Perfect harmony. Join our band. Deliver creativity to the world -- one note, one voice, one idea at a time. At Spotify, we focus relentlessly on building the best and most valuable experience available anywhere, enhancing every moment by connecting the world to the art and the creatives who shape it. Spotify transformed music listening forever when it launched in Sweden in 2008. Discover, manage and share over 70m tracks for free, or upgrade to Spotify Premium to access exclusive features including offline mode, improved sound quality, and an ad-free music listening experience. Today, Spotify is the most popular global audio streaming service with 365m users, including 165m subscribers across 178 markets. We are the largest driver of revenue to the music business today. Musicians Specialties: Music Streaming, Audio Platform, Podcasts, Data Analytics, Machine Learning, User Experience

Responsibilities

  • ● he 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.
  • ● Within Personalization, the Speak Team owns the development of Spotify's state-of-the-art speech models, contributing to speech recognition, speech synthesis, and speech-to-speech models. We craft voice models that match human-level emotional expressiveness, so we can deeply engage our listeners and support creators at scale. Our groundbreaking work on speech synthesis relies on state-of-the-art deep learning methods and evaluation techniques, highly efficient data processing and model serving, and capturing audio of outstanding quality from our voice talent pool.