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Conduct research in machine learning focusing on AI, develop models, design experiments, collaborate on product ideas, and mentor researchers.

The role involves designing and deploying machine learning systems for content safety at Spotify, collaborating with various stakeholders, and providing technical leadership.

Manage a team of 7–8 engineers building RightsDB and related rights systems. Own roadmap, delivery, platform operations, cross-functional partnerships, mentorship, and scaling content ingestion and compliance workflows for rights-protected and UGC content.

Provide strategic legal advice on music publishing and copyright licensing; draft, structure, and negotiate licensing agreements with CMOs, PROs, and publishers; advise on compliance, new product features, market launches, and commercial initiatives across digital platforms; partner with cross-functional teams including Business Affairs, Finance, and Product.

Design, build, and operate secure enterprise AI platform capabilities connecting models, agents, and internal systems. Own major infrastructure workstreams (MCP gateway, enterprise context), build backend services and APIs, enable identity-aware governance (access, permissions, auditing), design agentic workflows, and take operational ownership while partnering with stakeholders to scale dependable AI tooling across Spotify.

The role involves designing and implementing large-scale ML solutions for personalized music experiences, collaborating with cross-functional teams to enhance user interactions and fulfill music recommendations.

The Senior Staff Machine Learning Engineer will develop and scale ML systems for content classification, moderation, and decision-making, ensuring quality and compliance across Spotify's platform.

Design, build, and productionize personalized recommendation models and LLM-based experiences for Spotify's Home feed. Own model training, fine-tuning, evaluation, A/B testing, inference optimization, and ML platform/data pipeline improvements. Drive technical direction, mentor engineers, and collaborate with cross-functional partners to deliver scalable, cost-efficient personalization at global scale.