Staff Machine Learning Engineer

We design Spotify's consumer experience end-to-end, across every screen, platform, and partner integration. Our mission is to make listening feel effortless, personal, and joyful for billions of users worldwide.

The Content Platform team powers the full lifecycle of content across music, podcasts, audiobooks, and emerging formats at Spotify. We're seeking a Staff Machine Learning Engineer to build and scale foundational ML systems that power content understanding across Spotify.

In this role, you'll work on systems that generate deep, machine-readable understanding of content across audio, video, text, and images,enabling automation, improving quality, and unlocking new product experiences.

Responsibilities

• Build and scale machine learning systems that generate deep understanding of content across modalities
• Develop models for classification, tagging, semantic understanding, and content enrichment
• Create high-quality content enrichment at scale using LLMs and agentic systems
• Design systems that make content intelligence signals available to downstream teams and products
• Improve automation for content quality, safety, and metadata enrichment at scale
• Collaborate with product, policy, and engineering teams to translate content intelligence into user impact
• Contribute to evaluation frameworks, data pipelines, and annotation systems
• Support rapid experimentation to prototype and launch new types of content signals
• Help improve system reliability, scalability, and performance across large datasets

Requirements

• Experience building and deploying machine learning systems in production
• Comfortable working with ML frameworks such as PyTorch, TensorFlow, or similar
• Experience working with large datasets and care about data quality and evaluation
• Interested in or have worked with multimodal machine learning
• Understand how to design systems that balance automation with quality and user experience
• Comfortable working on complex problems with evolving requirements
• Think in systems and understand how models connect to product outcomes
• Communicate clearly and work well across technical and non-technical teams