Production ML Engineer, Personalization & Subscriptions

Spotify; Greater London; Hybrid; GBP 90,000 - 130,000; Full time

Job summary

Spotify is seeking a Machine Learning Engineer to join the Radius squad in the Subscriptions mission. You will own end-to-end ML initiatives, develop production models, and contribute to scalable ML capabilities powering personalization and optimization.

Responsibilities include leading multi-week ML projects, collaborating across design, data science, and engineering, and producing observable, reliable systems for hundreds of millions of users.

Qualifications

• Experience shipping production ML systems.
• Strong ML theory and practical know-how.
• Able to explain model intuition and assumptions.
• Capable of owning ML projects end-to-end.
• Clear communicator with stakeholders.
• Hands-on with PyTorch and Python/Scala.
• Experience building data pipelines.
• Familiar with cloud platforms (GCP/AWS).
• Comfort with agile processes.
• Driven to deliver business impact.

Responsibilities

• Lead multi-week ML initiatives end to end, translating business requirements into specs and shipping models.
• Own components of ML systems, ensure observability and reliability.
• Collaborate with cross-functional teams to build features.
• Prototype approaches and productionise at scale for hundreds of millions of users.
• Improve quality through testing and tooling.
• Unblock teammates and raise squad velocity.
• Use AI-assisted engineering to move faster while shipping quality.
• Partner with senior engineers and ML practitioners.

Skills

Production ML

ML theory/practice

Explainability

End-to-end ownership

Stakeholder comms

Growth mindset

Python/Scala

PyTorch

Data pipelines

Cloud platforms

Agile

Business impact

Tools

PyTorch

Python

Scala

GCP

AWS

Job description

Spotify is seeking a Machine Learning Engineer to join the Radius squad in the Subscriptions mission. You will own end-to-end ML initiatives, develop production models, and contribute to scalable ML capabilities powering personalization and optimization.

Responsibilities include leading multi-week ML projects, collaborating across design, data science, and engineering, and producing observable, reliable systems for hundreds of millions of users.