Staff Machine Learning Engineer - Content Intelligence in London
Staff Machine Learning Engineer - Content Intelligence

Staff Machine Learning Engineer - Content Intelligence in London

London Full-Time 80000 - 100000 £ / year (est.) Home office (partial)
Creandum

At a Glance

  • Tasks: Build and scale machine learning systems for content understanding across audio, video, text, and images.
  • Company: Join Spotify, a leader in creating effortless and joyful listening experiences.
  • Benefits: Flexible work environment, competitive salary, and opportunities for professional growth.
  • Other info: Collaborative culture with a focus on creativity and innovation in a dynamic tech environment.
  • Why this job: Make a real impact on millions of listeners with innovative machine learning solutions.
  • Qualifications: Experience in deploying ML systems and working with frameworks like PyTorch or TensorFlow.

The predicted salary is between 80000 - 100000 £ per year.

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.

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
Who You Are
  • 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
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.

Staff Machine Learning Engineer - Content Intelligence in London employer: Creandum

Spotify is an exceptional employer that fosters a culture of innovation and collaboration, empowering employees to shape the future of audio experiences for millions worldwide. With a focus on employee growth, Spotify offers opportunities to work on cutting-edge machine learning systems in a flexible environment, whether in London or Stockholm, ensuring a balance between professional development and personal well-being. Join us to be part of a team that values creativity, diversity, and the joy of listening.
Creandum

Contact Detail:

Creandum Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Staff Machine Learning Engineer - Content Intelligence in London

✨Tip Number 1

Network like a pro! Reach out to folks in the industry, especially those at Spotify. A friendly chat can open doors and give you insights that a job description just can't.

✨Tip Number 2

Show off your skills! If you've got a portfolio or projects showcasing your machine learning prowess, make sure to highlight them during interviews. Real-world examples speak volumes.

✨Tip Number 3

Prepare for technical challenges! Brush up on your ML frameworks like PyTorch or TensorFlow. Be ready to discuss how you've tackled complex problems in the past—it's all about demonstrating your expertise.

✨Tip Number 4

Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you're genuinely interested in being part of the Spotify team. Let's get you in there!

We think you need these skills to ace Staff Machine Learning Engineer - Content Intelligence in London

Machine Learning
Deep Learning
Model Development
Content Enrichment
Large Language Models (LLMs)
Data Quality Management
Multimodal Machine Learning
System Design
Automation
Collaboration
Data Pipelines
Evaluation Frameworks
Problem-Solving
Communication Skills

Some tips for your application 🫡

Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Staff Machine Learning Engineer role. Highlight your experience with ML frameworks like PyTorch or TensorFlow, and don’t forget to mention any work with large datasets!

Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about content intelligence and how your background makes you a perfect fit for our team. Keep it engaging and personal—let us see the real you!

Showcase Your Projects: If you've worked on relevant projects, make sure to include them in your application. Whether it's building ML systems or experimenting with multimodal machine learning, we want to see what you've done and how it relates to the role.

Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re serious about joining the StudySmarter family!

How to prepare for a job interview at Creandum

✨Know Your ML Frameworks

Make sure you brush up on your knowledge of ML frameworks like PyTorch and TensorFlow. Be ready to discuss your experience with these tools, as well as any projects where you've successfully deployed machine learning systems in production.

✨Showcase Your Problem-Solving Skills

Prepare to talk about complex problems you've tackled in the past. Think about how you approached evolving requirements and what strategies you used to balance automation with quality. Real-world examples will help demonstrate your thought process.

✨Understand Content Intelligence

Familiarise yourself with content intelligence and how it impacts user experience. Be prepared to discuss how you would design systems that enhance content understanding across different formats, and how this can lead to improved product outcomes.

✨Communicate Effectively

Since you'll be collaborating with both technical and non-technical teams, practice explaining complex concepts in simple terms. Clear communication is key, so think about how you can convey your ideas effectively during the interview.

Staff Machine Learning Engineer - Content Intelligence in London
Creandum
Location: London

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