Spotify
Tech / AI / Software
SeniorMachineLearningEngineer-MessagingPlatform
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“Senior Machine Learning Engineer - Messaging Platform at Spotify. Skills: machine learning models, experimentation, reinforcement learning, optimization. Design, build, and ship machine learning models that optimize messaging across push, email, and in-app channels. Plan and run A experiments in a multi-objective environment, balancing conversion, engagement, retention, and reachability”
What You'll Achieve.
optimize messaging across push, email, and in-app channels; balancing conversion, engagement, retention, and reachability; optimize for long-term user outcomes rather than immediate interactions
Industry & Context.
translating business problems into ML solutions; complex optimization problems; multi-objective decision-making; analyze results using approaches like causal inference or metric decomposition
What They're Looking For.
Must Have
experience building and deploying machine learning models in production environments at scale, translating business problems into ML solutions, design reliable tests in environments with interacting metrics, experience with PyTorch, experience with distributed systems such as Ray or similar frameworks
Nice to Have
curiosity about reinforcement learning and long-term optimization systems
What You'll Do.
and ship machine learning models that optimize messaging across push
Plan and run A experiments in a multi-objective environment
Contribute to reinforcement learning systems that optimize for long-term user outcomes rather than immediate interactions
Own the full ML lifecycle
from data and modeling to deployment
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
How You'll Work.
Team & Collaboration
Partner with product managers, data scientists, and engineers to define what success looks like and how to measure it; discussing trade-offs with cross-functional partners; working across disciplines
Communication Scope
discussing trade-offs with cross-functional partners
Full Job Description
## 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 ## Additional Information Spotify is an equal opportunity employer. You are welcome at
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