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
Skills Required
- Strong experience building and deploying machine learning models in production environments at scale
- Experience with PyTorch and distributed systems such as Ray
- Experience with complex optimization problems such as ranking systems or multi-objective decision making
- Understanding of experimentation and ability to design reliable tests
- Experience or curiosity about reinforcement learning
Spotify Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Spotify and has not been reviewed or approved by Spotify.
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Flexible Benefits — Employees consistently praise the total compensation package beyond base salary, highlighting a mix of RSUs, cash incentives, and stipends alongside core pay. The package is described as flexible and customizable through equity choices (e.g., RSUs, options, cash) that can be tailored for long-term wealth building.
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Leave & Time Off Breadth — Time-off offerings are repeatedly highlighted as substantial, including generous vacation, paid sick days, volunteer time, and flexible holidays. These policies are framed as a meaningful part of the overall rewards experience beyond salary.
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Healthcare Strength — Health coverage is portrayed as comprehensive, spanning medical, dental, vision, life insurance, disability coverage, and mental health support. Additional employer contributions to HSAs are cited as strengthening the overall health and wellness value proposition.
Spotify Insights
What We Do
Spotify transformed music listening forever when it launched in Sweden in 2008. Discover, manage and share over 50m tracks for free, or upgrade to Spotify Premium to access exclusive features including offline mode, improved sound quality, and an ad-free music listening experience.
