Spotify

Senior Machine Learning Engineer - Personalization

New York, NY · Senior

Sponsorship not specified$210k-$260kDetected 70 days ago

PythonJavaScalaGCPCloud PlatformsMachine LearningPyTorchSparkData ScienceNLPLLMsMLOpsStatisticsA/B TestingCollaboration

About the role

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 better than anyone else so that we can make great recommendations to every individual and keep the world listening.
The Surfaces Music team is responsible for music recommendations across Spotify's most visible surfaces, including Home and the Now Playing experience.

Contribute to the design, development, evaluation, and iteration of recommendation models - including candidate generation, ranking, and embedding models - powering music surfaces at scale.
Drive hands-on ML development to improve reward signals and recommendation quality across Home, Now Playing, and other core surfaces.
Collaborate with Data Science, Product, and Design partners to define success metrics, run A/B experiments, and translate insights into product improvements.
Partner with teams across Personalization to integrate and test new signals in recommendation systems.
Every day, hundreds of millions of people use the products we build, including destinations like Home and Search, original playlists like Discover Weekly and Daylist, and new innovations like AI DJ and AI Playlists.
We own music shelf and candidate generation as well as the ranking models that power these experiences.
Our models include embedding models for deep catalog discovery, new release recommendations, and a unified transformer-based generative personalization model that is poised to reshape how we deliver personalized experiences across Spotify.

You have some experience with large-scale distributed data processing frameworks such as Apache Beam, Apache Spark, or Scio, and cloud platforms like GCP or AWS.
You have experience collaborating across teams on complex ML projects and navigating cross-functional stakeholders.
You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what's playing in your headphones.

You have experience implementing ML systems in Java, Scala, Python, or similar languages.
Familiarity with PyTorch, Ray or Hugging Face is a plus.

You have hands-on experience building and shipping production machine learning systems at scale, ideally in personalization or recommendation systems.

This listing is sourced directly from Spotify's careers page and normalized into a canonical job model.