Role overview
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.
What you'll work on
Who You Are
- 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
Where You'll Be
- 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.
Spotify is an equal opportunity employer. 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. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It’s in our differences that we will find the power to keep revolutionizing the way the world listens.
At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know - we’re here to support you in any way we can.
Spotify transformed music listening forever when we launched in 2008. Our mission is to unlock the potential of human creativity by giving a million creative artists the opportunity to live off their art and billions of fans the chance to enjoy and be passionate about these creators. Everything we do is driven by our love for music and podcasting. Today, we are the world’s most popular audio streaming subscription service.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us. Find our AI notice here: https://lifeatspotify.com/ai-notice
Tags & focus areas
Used for matching and alerts on DevFound Engineer Machine Learning Aws Scala Pytorch Python R Gcp