Senior Machine Learning Engineer - Messaging Platform

Team: Subscriptions R&D

Location: London, Stockholm

Commitment: Permanent

Workplace Type: hybrid

What Youll 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 Youll 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