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A leading audio streaming service is seeking a Staff Machine Learning Engineer to define and drive the ML technical strategy for Search. The role involves building models that improve query understanding and relevance, while collaborating with a cross-functional team. Strong background in machine learning, experience with transformer models, and proficiency in programming languages like Java, Scala, or Python are essential. You’ll contribute to connecting millions of users with audio content each day.
The Personalization team at Spotify makes deciding what to play next effortless and enjoyable for every listener. We aim to deeply understand music, podcasts, audiobooks, and videos to deliver exceptional recommendations that keep hundreds of millions of people engaged every day. Our work spans across experiences like Home, Search, curated playlists such as Discover Weekly and Daylist, and new innovations like AI DJ and AI Playlists.
Search is one of the most important entry points into Spotify’s ecosystem—powering how listeners find and rediscover music, podcasts, and audiobooks. Beyond retrieval, Search drives exploration and discovery, connecting fans with creators in new ways. Building world-class Search means tackling natural language understanding, personalization, and generative AI at massive scale. Generative AI is also revolutionizing Spotify’s product capabilities and technical infrastructure, with generative recommender systems, agent frameworks, and LLMs opening significant opportunities to meet diverse user needs, expand use cases, and gain richer insights into our content and users
As a Staff Machine Learning Engineer in Search, you’ll focus on recommender systems modeling at the intersection of generative recommenders and foundational understanding of user taste across music and talk content. You will define and execute the ML technical strategy for Search, building the next generation of Spotify’s recommendation systems, user representations, and supporting technical architecture. Join us and you’ll help millions of users discover and connect with the world’s audio content every day.
What You'll Do