Staff Machine Learning Engineer – Personalized Listening Experiences

Spotify
Spotify

Job Overview

The Personalization team makes deciding what to play next easier and more enjoyable for every listener. From Daily Mix 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. Every day, hundreds of millions of people all over the world use the products we build which include destinations like “Home” and “Search” as well as original playlists such as “Discover Weekly” and “Daily Mix.” We’re a team of technologists, product insight specialists, designers, and product managers in Boston and New York.

What you will learn and do

  • Improve the quality of Spotify’s personalized listening recommendations in playlists for our huge number of listeners, across many countries
  • Prototype new approaches and productionize solutions at scale for our hundreds of millions of active users.
  • Provide technical leadership to machine learning engineers
  • Work closely with Product, User Research, Data Scientists, and other engineers to develop machine learning approaches that advance our mission to connect fans and artists
  • As part of the leadership team of a 50-person org, develop and help execute our long-term strategy and roadmap.
  • Be accountable for algorithmic fairness and responsibility of playlist content recommendations systems
  • Identify opportunities for platformization and communicate requirements to platform teams
  • Who You Are

  • You have a strong background in building content recommendation products with machine learning, especially systems that have served 1M+ users. You have 5+ years of machine learning experience, 3+ years in an industry setting.
  • You’re passionate about improving the experience of music listeners with personalization. 
  • You have hands-on experience implementing production machine learning content recommendations systems at scale in Java, Scala, Python, or similar languages. Experience with XGBoost, TensorFlow is also a plus.
  • You have experience with data pipeline tools like Apache Beam or even our open source API for it, Scio, and cloud platforms like GCP or AWS.
  • You care about agile software processes, data-driven development, reliability, and disciplined experimentation.
  • You keep up with state of the art research by reading papers, attending conferences, and participating in research communities.
  • Nice to have

  • Multimedia (audio, image, and/or video) recs experience
  • Strong passion for music
  • Published in top-tier machine learning conferences / journals
  • You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what’s playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be brilliant. So bring us your personal experience, your perspectives, and your background. It’s in our differences that we will find the power to keep revolutionizing the way the world listens.Spotify transformed music listening forever when we launched in 2008. Our mission is to unlock the potential of human creativity by giving a million creative artists the opportunity to live off their art and billions of fans the opportunity to enjoy and be inspired by these creators. Everything we do is driven by our love for music and podcasting. Today, we are the world’s most popular audio streaming subscription service with a community of more than 299 million users.

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