---
title: 'Machine Learning Engineer - Subscriptions at Spotify'
canonical: 'https://feeny.ai/job/machine-learning-engineer-subscriptions-spotify-london-fbsgsbqz0vrg'
type: 'job'
last_seen: '2026-10-24'
---

# Machine Learning Engineer - Subscriptions at Spotify

- **Company:** Spotify
- **Location:** London, United Kingdom
- **Work type:** hybrid
- **Posted:** 2026-10-23
- **Last confirmed live:** 2026-10-24
- **Apply:** https://jobs.lever.co/spotify/19c12e29-b6d4-4d97-9053-48238fb7c381

## Job description

At Spotify, our Subscriptions Mission focuses on creating experiences that help listeners discover the value of Spotify, become subscribers, and stay with us for the long term. By combining technology, experimentation, and a deep understanding of our users, we help connect artists and fans while building a sustainable subscription business.

Within the Subscriptions Mission, the Subs Foundational Models Product Area is part of the Subs User Understanding Studio. We build scalable machine learning solutions that personalize the subscriber journey, from conversion through to long-term retention. Working closely with teams across the mission, we develop ML solutions that improve key business metrics, including subscriber growth, monthly active users, and Premium retention.

We're looking for a Machine Learning Engineer to join our Radius squad. You'll take ownership of impactful ML initiatives, develop and improve production models, and contribute to the foundational ML capabilities that power personalization and optimization across Subscriptions.

Your work could include reducing friction for Free users while balancing retention and conversion, improving payment experiences to reduce Premium churn, or developing reusable models such as subscriber embeddings that support multiple products and use cases.

## What You'll Do

- Lead multi-week ML initiatives end to end, from translating business requirements into technical specifications to shipping models and measuring their impact on subscriber metrics
- Own components of our ML systems, making independent technical trade-offs and keeping them observable, reliable, and well documented
- Collaborate with a multi-functional agile team spanning user research, design, data science, product management, and engineering to build new product features that advance our mission to connect artists and fans in personalised and relevant ways
- Prototype new approaches and productionise solutions at scale for our hundreds of millions of active users
- Help drive optimisation, testing, and tooling to improve quality
- Unblock and share context with your teammates to raise the whole squad's velocity
- Use AI-assisted engineering to move faster and remove repetitive toil, while owning the quality of everything you ship
- Partner closely with senior and staff ML engineers, and be part of an active group of machine learning practitioners in your mission and across Spotify

## Who You Are

- You have experience building and shipping production ML systems
- You have a strong background in machine learning, theory, and practice
- You are comfortable explaining the intuition and assumptions behind ML concepts
- You can own well-scoped ML projects end to end and make sound technical decisions independently
- You communicate clearly with stakeholders and can explain the reasoning behind your technical choices
- You are curious, open to feedback, and keen to grow your scope over time
- You have hands-on experience implementing and maintaining production ML systems in Python, Scala, or similar languages, including model development with PyTorch
- You are experienced with building data pipelines, and you are self-sufficient in getting the data you need to build and evaluate your models
- You preferably have experience with cloud platforms like GCP or AWS
- You care about agile software processes, data development, reliability, and focused experimentation
- You have a desire to drive business impact

Where You'll Be

- We offer you the flexibility to work where you work best! For this role, you can be within the EMEA region as long as we have [a work location](https://lifeatspotify.com/being-here/work-from-anywhere)

- This team operates within the Central European and GMT time zone for collaboration.

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.

## About Spotify

## Company Overview
- **One-liner**: Spotify is the world's most popular audio streaming subscription service, connecting users to over 100 million tracks, 7 million podcast titles, and 700,000 audiobooks across 184 markets.
- **Entity Type**: Public (NYSE: SPOT)
- **Headquarters**: Stockholm, Sweden
- **Founded**: 2006
- **Founders**: Daniel Ek and Martin Lorentzon

## Core Business
- Primary industry: Audio streaming and digital media
- Target customers: B2C (consumers via Free and Premium tiers) and B2B (advertisers, artists, and labels through Spotify Advertising and Spotify for Artists)
- Mission: "To deliver creativity to the world—one note, one voice, one idea at a time."

## Products & Services
- **Spotify Free**: Ad-supported streaming of music, podcasts, and audiobooks
- **Spotify Premium**: Subscription tier with offline mode, improved sound quality, and ad-free listening
- **Spotify for Artists**: Analytics, promotion, and monetization tools for creators
- **Spotify Advertising**: Programmatic and self-serve ad platform for brands
- **Audiobooks**: Catalog of 700,000+ audiobook titles (market entry in 2022)

## Market Standing
- **Valuation/Market Cap**: Not disclosed in available sources; stock price reported at USD 391.23 (as of 2024-10-29)
- **Key Metric**: Annual Revenue EUR 17.2B; 777 million monthly users including 300 million subscribers (per Spotify Newsroom). Note: LinkedIn company data lists 365M users/165M subscribers — conflicting reports, likely reflecting an older snapshot.
- **Notable Investors/Partners**: Series A of USD 21.6M with 5 investors (2008); debt financing of USD 1.0B (2016); convertible notes in 2016 and 2021. Key acquisitions include Sonantic (2022), Mediachain (2017), and Tunigo (2013).
- **Growth Signals**: Headcount grew +14.2% YoY to 8,921 employees; 9 offices across 4 countries; expansion into audiobooks; 300M+ paying subscribers.

## Competitive Advantages
- Scale: largest audio streaming subscriber base globally
- Data and AI personalization: mature recommendation engines and AI-driven discovery
- Multi-format audio ecosystem: music, podcasts, and audiobooks in a single app
- Strong brand recognition and deep creator relationships

## Strategic Focus
- AI-powered personalization and generative audio tools
- Audiobook market expansion
- Podcast ecosystem growth
- Creator monetization and artist tools

## Why Work Here
- Employer rating 4.0/5.0 from 2,155 reviews (Work-Life: 4.2, Compensation: 3.9, Culture: 4.0, Career: 3.5)
- **Work

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