Machine Learning Engineer II, Personalization

The Personalization team makes deciding what to play next easier and more enjoyable for every listener. From Discover Weekly to AI DJ, 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.
Do you want to help Spotify invent the future of prompt based playlists and listening sessions? In this role, you will develop the engine behind the AI Playlist feature and help improve and expand the technology.

What You'll Do

• Contribute to the design, development, evaluation, and maintenance of the AI Playlist engine
• Stay abreast of the latest in LLM technology and apply it to the team’s problem domain
• Contribute broadly to the team, including developing tooling and going on-call
• Hands-on expertise with implementing end-to-end production ML systems at scale in Java, Scala, Python, or similar languages
• Experience with Pytorch, TensorFlow, Scikit-learn etc is a strong plus

Who You Are

• Strong background in Machine Learning, in particular experience with Large Language Models
• Hands on experience with Python, Flyte, and PyTorch
• Comfortable moving quickly from idea to prototype to production
• Product minded
• Dedicated to making the best possible product for our users
• T-shaped in either Backend or Data Engineering, or preferably both

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.

The United States base range for this position is $138,250- $197,500 Plus equity. The benefits available for this position include health insurance, six month paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, 13 paid flexible holidays, paid sick leave. These ranges may be modified in the future.