Staff Machine Learning Engineer, GenRecs

The Personalization team makes deciding what to play next on Spotify easier and more enjoyable for every listener. We seek to understand the world of music and podcasts better than anyone else so that we can make great recommendations to every individual and keep the world listening. Every day, hundreds of millions of people all over the world use the products we build which include destinations like Home and Search, original playlists like Discover Weekly and Daylist, and are at the forefront of new innovations like AI DJ and AI Playlists.

Generative AI is transforming Spotify's product capabilities and technical architecture. Generative recommender systems, agent frameworks, and LLMs present huge opportunities for our products to serve more user needs and use cases and unlock richer understanding of our content and users.

This Staff Machine Learning Engineer will focus on recommender systems modeling at the intersection of generative recommenders and foundational understanding of user taste across music and talk content formats. You will work closely with a cross-functional team to define and execute the machine learning technical strategy for the product area, building the next generation of Spotify content and user representations and the technical architecture to support it.

Join us and you'll keep millions of users listening to great recommendations every day.

What You'll Do

• Contribute to defining the machine learning technical strategy at the intersection of generative recommenders and foundational user modeling
• Collaborate with a cross functional agile team spanning user research, design, data science, product management, and engineering to build new product features that connect fans and artists in personalized, meaningful ways
• Provide expert technical leadership and direction to accelerate development, ensure scalability and push the boundaries of current methods
• Contribute to designing, building, evaluating, shipping, and refining Spotify's personalization products by hands-on ML developmentPrototype new modeling approaches and productionize solutions at scale for our hundreds of millions of active users
• Promote and role-model best practices of ML model development, testing, evaluation, etc., both inside the team as well as throughout the organization
• Engage with the broader ML community within Spotify and stay current with ML research to inspire and evolve our approaches

Who You Are

• You have a strong background in machine learning and recommender systems, and you know how to bridge research and end-user impact
• You have production experience developing large-scale machine learning systems in Java, Scala, Python, or similar languages. Experience with PyTorch, Tensorflow, JAX is a strong plus
• You have hands-on experience training and operating transformer models in production settings, or a strong interest in doing so
• You enjoy leading projects from start to finish working closely with your team and peers
• You are comfortable dealing with ambiguity on high impact projects
• You're a strong communicator and systems thinker who can drive alignment and influence across technical and product stakeholders
• You care about agile software processes, data-driven development, reliability, and disciplined experimentation
• You stay current on ML trends and are eager to apply emerging ideas to Spotify's challenges
• You're passionate about the opportunity to enrich the listening experience for users around the world

Where You'll Be

• We offer you the flexibility to work where you work best! For this role, you can be within the North America region as long as we have a work location.
• This team operates within the Eastern Standard time zone for collaboration.