Machine Learning Engineer - Subscriptions

Description

The company is the company's Subscriptions Mission, which works on experiences that help listeners see the value of Premium, subscribe, and keep subscribing over time, balancing technology, experiments, and user insight to link artists and fans while growing a sustainable subscription business.

The Subs Foundational Models Product Area sits inside the Subs User Understanding Studio. The team builds scalable ML solutions that personalise the subscriber journey from conversion to long-term retention, and works with teams across the mission to lift subscriber growth, monthly active users, and Premium retention.

You would join the Radius squad as a Machine Learning Engineer, owning ML initiatives with real impact, building and improving production models, and contributing to the core ML capabilities behind personalisation and optimisation across Subscriptions.

Example work includes lowering friction for Free users while protecting retention and conversion, improving payment flows to cut Premium churn, and building reusable models such as subscriber embeddings that serve several products.

Responsibilities

• Lead multi-week ML initiatives from start to finish, turning business requirements into technical specs and measuring how shipped models move subscriber metrics
• Own parts of the ML systems, make technical trade-offs on your own, and keep them observable, reliable, and well documented
• Work in a cross-functional agile team with user research, design, data science, product management, and engineering to build features that connect artists and fans in personal, relevant ways
• Prototype new approaches and take them to production at scale for hundreds of millions of active users
• Drive optimisation, testing, and tooling that raise quality
• Remove blockers and share context so the whole squad moves faster
• Use AI-assisted engineering to cut repetitive work, while taking responsibility for the quality of what you ship
• Work closely with senior and staff ML engineers and join a community of ML practitioners across the mission and the company

Requirements

• You have built and shipped production ML systems
• You have a solid grounding in machine learning theory and practice
• You can explain the intuition and assumptions behind ML concepts
• You can own well-scoped ML projects end to end and make sound technical calls independently
• You communicate clearly with stakeholders and explain why you chose what you chose
• You are curious, take feedback well, and want to grow your scope over time
• You have hands-on experience building and maintaining production ML systems in Python, Scala, or a similar language, including model development in PyTorch
• You have built data pipelines and can get the data you need to build and evaluate models yourself
• You preferably have experience with cloud platforms such as GCP or AWS
• You care about agile processes, data development, reliability, and focused experimentation
• You want to drive business impact

Conditions

You can work from anywhere in the EMEA region, as long as there is a work location available

The team works within Central European and GMT time zones for collaboration

The company is an equal opportunity employer and welcomes candidates regardless of background. Accommodations are available at any stage of the application or interview process on request.