Spotify

Senior Machine Learning Engineer focused on building production-grade machine learning systems for conversational and agentic AI experiences, including user intent interpretation, context management, multi-turn interactions, and tool orchestration. The role involves creating evaluation frameworks and balancing experimentation with production rigor.

Machine Learning Engineering Manager for the Personalization team, focusing on building and scaling ML systems for recommendations and safety across Spotify's core surfaces and generative AI experiences. The role involves managing teams that develop synthetic data, fairness, and responsible AI approaches.

Engineering Manager to lead a Research Engineering team focused on generative AI for music. The role involves managing engineers, owning the roadmap, ensuring efficient training pipelines, and transitioning research prototypes into production features for millions of users. The team works on state-of-the-art generative technologies for music, focusing on artist-first principles, partnerships, choice, fair compensation, and artist-fan connection.

Senior Staff Machine Learning Engineer at Spotify focusing on recommender systems modeling at the intersection of generative recommenders and foundational understanding of personalization across music and talk content formats. The role involves defining and executing ML technical strategy, building next-generation content and user representations, and supporting technical architecture. Responsibilities include hands-on ML development, prototyping, productionizing solutions, and providing technical leadership.

Staff Machine Learning Engineer on the Policy & Safety team at Spotify, focusing on building systems for content moderation, policy enforcement, compliance, and safety-by-default. The role involves working with detection models, collaborative and agentic features, and ensuring safety is integrated into new product experiences.

Staff Machine Learning Engineer to build and scale foundational ML systems for content understanding (audio, video, text, images) at Spotify, enabling automation, improving quality, and unlocking new product experiences for millions of listeners and creators.

Senior Machine Learning Engineer on the Policy & Safety team, focusing on building ML-driven systems for content moderation, policy enforcement, and regulatory compliance within Spotify's consumer experience. This role involves working at the intersection of ML, platform engineering, and compliance to ensure safety and trust across the platform.

Spotify is seeking a Backend Engineer for its Artist-First AI Music lab to design and build state-of-the-art generative music products. The role focuses on creating new listening experiences for fans and artists, emphasizing artist partnerships, fair compensation, and artist-fan connection through AI tools. The engineer will contribute to shipping AI-powered music products.

Senior Machine Learning Engineer focused on personalization for Spotify's music and podcast features, building recommendation systems and conversational playlist generation tools for hundreds of millions of users.

Director of Machine Learning Engineering for Spotify's Surfaces Foundation team, focusing on personalized recommendation systems that power hundreds of millions of listeners. The role involves leading a group that shapes AI-driven recommendations across all Spotify surfaces, balancing ML infrastructure with product experience and enabling other teams to move faster.

Machine Learning Engineer for Spotify's Personalization team, focusing on improving music and podcast recommendations and search experiences. The role involves bringing emerging search and agentic experiences to a mature state, exploring, defining, building, validating, and optimizing new ideas.

Senior Staff Machine Learning Engineer at Spotify focused on building an agent-powered platform for personalized listening experiences, including features like DJ, Search, and AI Playlists. The role involves working on a shared Agent Engine that powers agent-based experiences across the company, integrating distributed systems, ML, and user experience.

Machine Learning Engineer on the Personalization team at Spotify, focusing on the Samba engine which powers recommendations, autoplay, radio, and personalized mixes. The role involves complex sequencing and optimization problems, balancing user preferences with business and creator needs, and delivering real-time personalization at scale.

Staff Machine Learning Engineer on the Personalization team at Spotify, focusing on recommendation systems for music and podcasts to improve user satisfaction and engagement. The role involves prototyping and productizing state-of-the-art ML models.

Machine Learning Engineer for Spotify's Music Promotion team, focusing on building systems to understand and predict promotion performance for creators, providing actionable insights and data-driven solutions.

Machine Learning Engineering Manager for Spotify's Surfaces Music team, focusing on building and scaling systems for music recommendations across key experiences like Home and Now Playing. The role involves candidate generation, ranking, and embedding models, with a focus on transformer-based personalization for millions of listeners.

Machine Learning Engineer on the Personalization team at Spotify, focusing on recommendation systems to improve user satisfaction. The role involves designing, building, evaluating, integrating, and refining reward signals for recommendations, with a focus on A/B testing and integrating mid-term signals. Requires hands-on ML development and production ML systems experience.

Machine Learning Engineer on the Personalization team at Spotify, focusing on using LLMs for content understanding (music, podcasts, audiobooks) to improve recommendations and user experiences. The role involves hands-on ML development, fine-tuning, RAG, and building scalable systems.

Senior Machine Learning Engineer role focused on optimizing ad loads for users on Spotify's audio and video platform. The role involves designing and implementing ML systems for ad performance, researching optimization strategies, analyzing user behavior with ML, and collaborating with cross-functional teams. Requires expertise in applied ML, software engineering, data analysis, Python/Java/Scala, Tensorflow/PyTorch, and data pipelines (Beam/Spark). Experience with LLMs, Ray, Adtech, or Recommender Systems is a plus.