Machine Learning Engineer hos Spotify


Data & Analytics / Engineering & IT / Machine Learning / Software Engineering in Boston, USA
“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 and podcasts better than anyone else so that we can make great recommendations to every individual person and keep the world listening. Everyday, 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 experts, designers, and product managers in Boston, New York, Stockholm, and London.”
What you’ll learn and do
  • Contribute to designing, building, evaluating, shipping, and refining Spotify’s product by hands-on ML development
  • Collaborate with a cross functional agile team spanning user research, design, data science, product management, and engineering to build new product features that advance our mission to connect artists and fans in personalized and relevant ways
  • Prototype new approaches and production-ize solutions at scale for our hundreds of millions of active users
  • Help drive optimization, testing, and tooling to improve quality
  • Be part of an active group of machine learning practitioners in Boston (and across Spotify) collaborating with one another

Who you are
  • You have a strong background in machine learning, with experience and expertise in personalized machine learning algorithms, especially recommender systems.
  • You have hands-on experience implementing production machine learning systems at scale in Java, Scala, Python, or similar languages. Experience with XGBoost, TensorFlow is also a plus.
  • You preferably 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 love your customers even more than your code

We are proud to foster a workplace free from discrimination. We strongly believe that diversity of experience, perspectives, and background will lead to a better environment for our employees and a better product for our users and our creators. This is something we value deeply and we encourage everyone to come be a part of changing the way the world listens to music.
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