Machine Learning Engineer - Subscriptions

The Subscriptions Mission team builds and evolves Spotify’s subscription products to drive growth, retention, and user value. We focus on creating seamless, personalized experiences that help listeners discover the right plan and get the most out of Spotify, while enabling sustainable business growth.

You’ll join the User Understanding space within the Subscriptions Mission, where we build machine learning systems that personalize the subscription journey for millions of listeners. Sitting in the Lorax squad, this team focuses on optimizing the full subscription funnel—from discovery to conversion—by delivering relevant, timely, and meaningful experiences. Our work directly impacts how users engage with Spotify and how we grow our subscriber base.

Contribute to designing, building, evaluating, and improving machine learning models that power personalization across the subscription funnel

Work closely with a cross-functional team of engineers, data scientists, product managers, designers, and researchers to ship impactful features

Prototype new machine learning approaches and scale them to production for hundreds of millions of users

Help optimize experimentation frameworks, testing strategies, and tooling to improve model quality and reliability

Build and maintain robust data pipelines and production-ready ML systems

Participate in knowledge sharing within the machine learning community across Spotify

Contribute to improving how we personalize messaging, offers, and user journeys across discovery and conversion surfaces

You have 3+ years of experience applying machine learning in production environments

You are comfortable explaining machine learning concepts, assumptions, and trade-offs to both technical and non-technical partners

You have hands-on experience building and maintaining production ML systems using Python, Scala, or similar languages

You have experience working with modern ML frameworks such as PyTorch or distributed systems like Ray

You are experienced in building data pipelines and independently sourcing and preparing data for modeling

You have worked with cloud platforms such as GCP or AWS

You care about experimentation, iteration, and using data to guide decisions

You enjoy working in collaborative, cross-functional teams and contributing to shared outcomes

You are motivated by driving measurable business impact through your work

This role is based in New York or Boston

We offer you the flexibility to work where you work best! There will be some in person meetings, but still allows for flexibility to work from home.

The United States base range for this position is 148,901–212,716 USD, 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, paid flexible holidays, and paid sick leave. These ranges may be modified in the future.