Senior Staff Machine Learning Engineer, Content Platform

Spotify; Greater London; Hybrid; GBP 60,000 - 80,000; Full time

Job summary

Spotify is looking for an experienced Machine Learning Engineer to shape the content understanding strategy and build scalable machine learning systems. You will develop automated systems ensuring content quality and collaborate with cross-functional teams to enforce content standards. Ideal candidates have strong experience in production-grade machine learning systems and knowledge of modern ML frameworks like PyTorch or TensorFlow. The position allows flexibility in working from home while being based in London or Stockholm.

Qualifications

• Strong experience building production-grade machine learning systems at scale.
• Experienced with modern ML frameworks such as PyTorch, TensorFlow, or JAX.
• Understanding of multimodal machine learning.

Responsibilities

• Shape the machine learning strategy for content understanding and platform-level decisioning.
• Build & scale ML systems for classification, moderation, ranking, risk detection.
• Design and deploy models across text, audio, image, and video domains.

Skills

Machine Learning Systems

Production-Grade ML Frameworks

Multimodal Machine Learning

System Design

Data Quality

Tools

PyTorch

TensorFlow

JAX

Job description

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.

What You Will Do

• Shape the machine learning strategy for content understanding and platform-level decisioning
• Build & scale ML systems for classification, moderation, ranking, risk detection across multimodal content
• Develop automated decisioning systems that ensure content quality, integrity, & policy compliance at scale
• Design and deploy models across text, audio, image, and video domains
• Build systems that enable controlled, reliable access to content and metadata for downstream applications
• Collaborate with product, policy, trust & safety teams to operationalize content standards across platform
• Improve automation to reduce manual intervention while maintaining high standards of trust and quality
• Mentor engineers and contribute to best practices in ML engineering, evaluation, and system design

Who You Are

• You have strong experience building production‑grade machine learning systems at scale
• You are experienced with modern ML frameworks such as PyTorch, TensorFlow, or JAX
• You have worked with or are interested in multimodal machine learning
• You understand how to design systems that balance automation with quality, safety, and user experience
• You are comfortable working on complex, ambiguous problems with high impact
• You think in systems, connecting models to platform-level outcomes and user experiences
• You care deeply about data quality, evaluation rigor, and system reliability
• You communicate clearly and influence across technical and non‑technical teams

Where You Will Be

• This role is based in London or Stockholm
• We offer you the flexibility to work where you work best! There will be some in‑person meetings, but still allows for flexibility to work from home.