Machine Learning Engineer, Content and Catalog Management

The Catalog and Content Management (CoCaM) team works at the heart of the Content Platform R&D studio, the central point for the ingestion, distribution, management, knowledge and growth of all content you experience through Spotify products. In CoCaM we drive the management of content and make decisions that impact the whole of Spotify on all content's appropriateness, availability, quality and accuracy. Through reactive and proactive reporting mechanisms we use the knowledge of Content Platform and apply platform & business policy with content, user, financial and experiential context to make and store a decision best for Creators, Consumers and Spotify.

Location:

• London

Job type: Permanent

This is an outstanding opportunity to contribute to the development and application of ML within our content and catalogue management platform. You'll be at the forefront of driving impactful solutions, while collaborating within a dynamic and supportive team environment.

What You'll Do:

• Drive the full lifecycle of ML solutions for CoCaM services, including research, design, development, evaluation, and deployment.
• Manage Machine Learning projects ranging from Supervised Learning, to Reinforcement Learning, to LLMs.
• Optimize and monitor deployed ML model performance, implementing improvements based on analysis.
• Document and standardize ML processes, pipelines, and model specifications.
• Collaborate with cross-functional teams spanning research, engineering, data science, product managers and other stakeholders to understand business needs and identify opportunities for ML applications.
• Work closely with engineering teams to integrate ML models into existing systems and workflows.
• Be an active participant of a group of machine learning engineers, staying updated with the latest advancements, participating in code reviews, and contributing to knowledge sharing across the team.

Who You Are:

• 2+ years of hands-on experience in developing and deploying machine learning models in a production environment.
• Practical experience in implementing ML systems using languages like Python or Scala and are familiar with relevant ML libraries and frameworks (e.g., TensorFlow or PyTorch).
• Solid understanding of various machine learning algorithms (e.g., classification, regression, clustering) and their practical applications.
• Proficient in data manipulation and analysis using tools like SQL and Pandas.
• Broad ML skillset and are happy to work on all aspects of ML problems. Not only modeling, but also feature work in data pipelines, some implementation in data pipeline workflows, experimentation setup and analysis.
• Experience with model evaluation metrics and techniques for ensuring model quality and generalization.
• Experience with cloud platforms (e.g., GCP, AWS, Azure) and their ML services.
• Comfortable communicating technical concepts clearly and effectively within the team and with non-technical stakeholders.
• Proactive problem-solver with a strong sense of ownership and a drive to learn.

Where You'll Be:

• This role is based in London (UK)
• 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.

Extensive learning opportunities, through our dedicated team, GreenHouse.

Flexible share incentives letting you choose how you share in our success.

Global parental leave, six months off - fully paid - for all new parents.

All The Feels, our employee assistance program and self-care hub.

Flexible public holidays, swap days off according to your values and beliefs.

Learn about life at Spotify.

You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what's playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It's in our differences that we will find the power to keep revolutionizing the way the world listens.

Spotify transformed music listening forever when we launched in 2008. Our mission is to unlock the potential of human creativity by giving a million creative artists the opportunity to live off their art and billions of fans the chance to enjoy and be passionate about these creators. Everything we do is driven by our love for music and podcasting. Today, we are the world's most popular audio streaming subscription service with a community of more than 500 million users.