Spotify

Tech / AI / Software

SeniorMachineLearningEngineer-MessagingPlatform

london, england, united kingdom; stockholm, stockholm, sweden Permanent Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“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.

Tech / AI / Software
Problems you'll solve

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

Free ATS check

Applying for this Senior Machine Learning Engineer - Messaging Platform role?

Most applicants get filtered before a human reads their resume. See if yours makes the cut.

How to Apply on Lever

  • Lever uses a streamlined one-page form — apply in under 5 minutes.
  • LinkedIn import works well; review parsed data before submitting.
  • The cover letter field is optional but visible to reviewers — use it to differentiate.
  • Referral codes from employees can significantly boost visibility of your application.

ANONYMOUS · UNFILTERED

What do employees actually say about Spotify?

Real rants from real employees. Read before you apply.

Read Company Rants →