Machine Learning Engineer, Personalization

The Safe-and-Sound team makes Spotify safe and enjoyable for every listener. From podcast recommendations to AI Playlists, we’re a part of some of Spotify’s most-loved features. We build Responsible AI solutions by understanding our music, podcasts and users better than anyone else. Join us and you’ll keep millions of users listening by making recommendations safe for each and every one of them.

What You'll Do

Contribute to deg, 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 New York (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 care about agile software processes, data-driven development, reliability, and disciplined experimentation

Where You'll Be

We offer you the flexibility to work where you work best! For this role, you can be within the North America region as long as we have a work location. This team operates within the Eastern Standard time zone for collaboration.