machine learning engineer for content safety

Spotify is the world’s most popular audio streaming subscription service. Its Content Platform manages the lifecycle of music, podcasts, audiobooks, and emerging content formats, helping keep content trusted, safe, compliant, and high quality for listeners worldwide.

• Define and drive machine learning strategy for safety, policy enforcement, and compliance systems;
• Build and scale ML systems for content detection, classification, and risk assessment;
• Develop automated decisioning systems for consistent and reliable policy enforcement;
• Design systems for real-time and large-scale content evaluation;
• Collaborate with product, policy, and trust and safety teams to operationalize content standards;
• Improve automation to reduce manual intervention while maintaining high quality and safety standards;
• Drive best practices in evaluation, fairness, and system reliability;
• Mentor engineers and contribute to technical direction across teams.

• Strong experience building production-grade machine learning systems at scale;
• Experience with modern ML frameworks such as PyTorch, TensorFlow, or similar;
• Experience working on systems where ML outputs influence real-world decisions;
• Understanding of designing systems that balance automation with safety and user experience;
• Comfort working on complex, ambiguous, high-impact problems;
• Systems thinking and understanding of how models connect to platform-level outcomes;
• Attention to data quality, evaluation rigor, and system reliability;
• Clear communication and ability to influence technical and non-technical teams.

• The role is based in London or Stockholm;
• Some in-person meetings with flexibility to work from home.