Staff Machine Learning Engineer - Content Intelligence

We design Spotify’s consumer experience—end to end, moment to moment, across every screen, platform, and partner integration. Our mission is to make listening feel effortless, personal, and joyful for billions of users around the world. That means turning complexity into clarity across hundreds of touchpoints—from our mobile and desktop apps to the smart speakers, TVs, cars, and integrations where Spotify shows up every day. If it touches a consumer, we shape it. We bring deep insight into human behavior, design, and technology to craft experiences that feel intuitive, expressive, and unmistakably Spotify.

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.

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

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 in 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