Spotify has 45 active AI-related job listings, with a significant focus on roles related to agents, comprising 42% of the openings, and application development, at 38%. The majority of these positions are within Engineering. The company is actively hiring for roles involving recommender systems, agent orchestration, and model serving. Over the last 30 days, Spotify has added 24 new AI roles, representing a 41% increase compared to the previous 30-day period.
Currently tracking 37 active AI roles, with 77 new openings in the last 4 weeks. Primary focus: Ship · Engineering. Salary range $110k–$402k (avg $223k).
Spotify currently has 41 active AI-related roles in our index. The most common open titles are: Machine Learning Engineer (2), Machine Learning Engineer, Personalization, Samba (2), Research Scientist - Music (2), Senior Machine Learning Engineer - Policy & Safety (2), Senior Research Scientist - Music (2). Most positions are in Engineering and Research.
Spotify's active AI hiring is concentrated in: agents (39%), application (34%), post-training (15%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Spotify is hiring AI talent in: United States (24 roles), Sweden (15 roles), United Kingdom (14 roles), Canada (1 role).
Job postings at Spotify most frequently reference: recommender systems, model serving, agent orchestration, multimodal, llm observability.
In the past 30 days, Spotify has posted 7 new AI-related roles. That is a -78% change versus the prior 30 days (32 → 7).
| Title | Stage | AI score |
|---|---|---|
| Senior Machine Learning Engineer, Personalization, Magenta 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. | AgentEval Gate | 8 |
| Senior Staff Machine Learning Engineer 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. |
| AgentPost-train |
| 8 |
| Staff Machine Learning Engineer - Policy & Safety 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. | AgentServe | 7 |
| Senior Machine Learning Engineer - Policy & Safety 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. | AgentData | 7 |
| Senior Staff Machine Learning Engineer - Agentic Systems 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. | Agent | 7 |
| Machine Learning Engineer, Personalization, Minesweeper 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. | Agent | 7 |