Machine Learning Engineer · Spotify

Fri, 24 Apr 2026 12:20:16 GMT
Engineering

Spotify · North America · $148,901-$212,716 · remote

The Personalization team makes deciding what to play next easier and more enjoyable for every listener. From Blend to Discover Weekly, 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.

Samba sits at the heart of Spotify’s personalization engine, powering experiences like autoplay, radio, and personalized mixes. We work on complex sequencing and optimization problems,balancing what users love with how Spotify supports creators and the business.

Our team blends machine learning, backend engineering, and data expertise, and collaborates across North America and Europe to deliver impactful, real-time personalization at scale.

Responsibilities

Design and build machine learning systems that optimize ranking and sequencing across personalized surfaces

Develop multi-objective optimization strategies that balance user satisfaction with business outcomes

Collaborate closely with cross-functional partners including product, data science, and engineering teams to align on goals, share context, and deliver impactful solutions

Work across ML, backend, and data layers to bring models into production

Contribute to scalable infrastructure supporting high-volume user interactions

Run experiments and use insights to continuously improve performance

Help shape technical direction and raise the bar for engineering excellence within the team

Requirements

5+ years of experience in machine learning, data, or backend engineering

Experienced with production-grade systems and scalable architectures

Worked on recommendation systems, ranking, or optimization problems

T-shaped skillset across ML, data, and backend domains

Comfortable navigating ambiguity and solving complex problems

Care about user experience and measurable impact

Enjoy collaborating across disciplines and geographies