The Content Platform team powers the full lifecycle of content across music, podcasts, audiobooks, and emerging formats at Spotify. We ensure that everything from licensed catalog to user-generated content is trusted, safe, and high quality for millions of listeners worldwide. Our systems are responsible for how content is ingested, understood, enriched, governed, and distributed across the platform. As the scale and diversity of content continues to grow - driven by advances in AI and new creation tools - we're building intelligent systems that can evaluate, manage, and route content reliably at global scale.
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. This work is central to delivering safe, high-quality, and differentiated experiences for millions of listeners and creators worldwide.
What You Will Do
- 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
Qualifications
- You have experience building and deploying machine learning systems in production
- You are comfortable working with ML frameworks such as PyTorch, TensorFlow, or similar
- You have experience working with large datasets and care about data quality and evaluation
- You are interested or have worked with multimodal machine learning
- You understand how to design systems that balance automation with quality and user experience
- You are comfortable working on complex problems with evolving requirements
- You think in systems and understand how models connect to product outcomes
- You communicate clearly and work well across technical and non-technical teams
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