As a Machine Learning Engineer in our Content Understanding teams, you will help define and build ML deployed at scale in support of a broad range of use cases driving value in media and catalog understanding.
Here are some examples of the work you may support: Audio fingerprinting to understand what music is played in podcasts enabling musicians to get royalties, Video and image tagging to understand what is happening in any video on Spotify for moderation and recommendations, Audiobook Author attribution using graph ML approaches for search and recommendations, Categorizing tracks in the catalog to know which are functional content or music tracks leveraged in royalty calculations and in search and recommendations.
Our teams are composed of product, machine learning, data and backend engineers, and subject matter experts who average 11 years behind the scenes in the music industry.
We are looking for a Machine Learning Engineer to help us define and build Spotify’s capabilities in this area. Our team expands the state of the art in AI-based machine technology, which enables intelligent, efficient, and intuitive ways to search, re-use, explore or process metadata. You 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.