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.

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.

• 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.

• 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.

• 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.