Have you ever had a debate at a party about who originally wrote a song versus who covered it? Tried to find a sample you loved more than the song you heard it in? Wondered who was actually in the recording booth for your favorite song (on both sides of the glass)? Wonder what Britney Spears, Nsync, Pink, Katy Perry, Taylor Swift, and The Weeknd all have in common? (The same songwriter wrote Billboard number-one singles for all of them). Who gets paid every time we sing “Happy Birthday”?
Music attribution at scale is one of the great unsolved technical problems of the music industry, and we’re building cutting-edge technology to solve it. Our goal is to solve this problem for the more than 60 million music tracks playable on Spotify, building a knowledge graph through cutting-edge machine learning models, deep subject matter expertise, and close integration with human-in-the-loop processes across Spotify and the industry. Content Platform’s catalog data powers Spotify experiences from Artist pages in the app, search and recommendations, human playlist curation, Spotify for Artists, and our music industry strategy.
We are looking for a Machine Learning Engineering Manager to help us lead teams in support of Spotify’s Music Knowledge Graph. Our team employs state of the art in AI-based machine technology, which enables intelligent, efficient, and intuitive ways to search, re-use, explore or process metadata. Engineers will use world-class engineering and machine learning techniques on real-world, internal, and external big data to directly impact the evolution of our music catalog.