Senior Machine Learning Engineer - Messaging Platform
Spotify
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This role on the market
32 open messaging roles across 17 companies are on ApplySarthi right now.
- Full-stack Engineer 4, Marketing and MessagingCapitalone
- Senior Data Engineer - Storage & MessagingBitvavo
- Product Manager, MessagingCreatoriq
- Senior Engineering Manager, Messaging ExperienceBraze
What messaging roles keep asking for: TypeScript (47%), Observability (34%), React (34%), Product management (31%), Rails (31%), Kubernetes (28%), AWS (25%), CI/CD (25%) — counted across their open postings here.
Machine Learning Engineer jobs in the United Kingdom · Machine Learning Engineer jobs in London · Remote Machine Learning Engineer jobs · Machine learning jobs · PyTorch jobs
Spotify has 36 open roles listed here.
- Senior Staff Engineer - Platform & Partner Experience
- Staff Engineer - Content Platform
- Staff Backend Engineer - Content Platform
- Senior Web Engineer - Subscriptions
- Senior Staff Machine Learning Engineer - Content Platform
Counted across 14 company job boards, updated as roles open and close.
Preparing for this interview
Interviews for messaging roles keep coming back to TypeScript, Observability, React, Product management. Practise those questions before you sit with Spotify.
Questions you are likely to be asked
- Why do you want to join Spotify?
- What is your experience with Machine learning? Tell me one thing you learned the hard way.
- Walk me through a model you built, from the data to how it was used.
- How did you know your model was actually good, and not just good on your test set?
- Tell me about a time the data was messy or wrong. What did you do?
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Practise the Senior Machine Learning Engineer - Messaging Platform at Spotify interview free →Spotify’s Subscriptions Mission focuses on converting listeners into lifelong subscribers by delivering seamless, valuable experiences across pricing, packaging, and customer journeys. We build the systems and tools that power acquisition, retention, and overall subscription growth at scale. The Messaging Platform powers Spotify’s communications to over a billion users — from push notifications to emails and in-app messages that connect listeners to the content they love. Within this space, the Paloma squad focuses on message optimization: deciding which message reaches which user, through which channel, and at what moment. We’re evolving how messaging works at Spotify — moving from short-term optimization toward systems that understand long-term user journeys. By combining reinforcement learning approaches with deeper domain signals, we’re expanding how machine learning shapes the entire messaging funnel. What You'll Do Design, build, and ship machine learning models that optimize messaging across push, email, and in-app channels Plan and run A/B experiments in a multi-objective environment, balancing conversion, engagement, retention, and reachability Contribute to reinforcement learning systems that optimize for long-term user outcomes rather than immediate interactions Partner with product managers, data scientists, and engineers to define what success looks like and how to measure it Own the full ML lifecycle, from data and modeling to deployment, monitoring, and iteration Integrate ML models with upstream systems, including domain value signals and opportunity generation frameworks Help shape the future of AI-assisted development within the team, exploring how tools can accelerate experimentation and delivery Who You Are You have strong experience building and deploying machine learning models in production environments at scale You are comfortable translating business problems into ML solutions and discussing trade-offs with cross-functional partners You have worked on complex optimization problems such as ranking systems or multi-objective decision-making You bring hands-on experience with PyTorch and distributed systems such as Ray or similar frameworks You understand experimentation deeply and can design reliable tests in environments with interacting metrics You are able to analyze results using approaches like causal inference or metric decomposition when needed You have experience with or curiosity about reinforcement learning and long-term optimization systems You enjoy working across disciplines and navigating ambiguity while shaping strategy and direction Where You'll Be This role is based in London and Stockholm 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 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. Find more English Speaking Jobs in United Kingdom on Arbeitnow
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Listed on arbeitnow · posted 2026-11-07. ApplySarthi collects openings and links to application pages; the role is advertised by Spotify, not by us.