Staff Machine Learning Engineer

The Personalization team at Spotify aims to make content discovery effortless and enjoyable for every listener. By deeply understanding music podcasts audiobooks and videos we deliver exceptional recommendations that keep millions of people worldwide engaged with our products daily. Our work spans experiences like Home Search curated playlists such as Discover Weekly and Daylist and cutting-edge innovations including AI DJ and AI Playlists.

Home plays a pivotal role in shaping the technical vision and architecture of recommendation systems that power the Spotify Home page. You’ll work on foundational components that enable the larger Home experience user activation listening habits across content types and expanding its technology to take advantage of LLMs and other Generative Recommender products. As a Staff Machine Learning Engineer in Home you’ll focus on recommender systems modeling at the intersection of generative recommenders and a foundational understanding of user taste across music and talk content.

You will define and execute the ML technical strategy for Home 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

• Define and drive the ML technical strategy for Home focusing on generative recommendation approaches

• Build models that improve user representations personalization and relevance across Spotify’s experiences

• Collaborate with a cross-functional agile team spanning user research design data science product management and engineering

• Prototype and productionize new modeling approaches at scale serving hundreds of millions of users worldwide

• Lead high-impact projects from ideation through deployment setting best practices for ML development testing evaluation and experimentation

• Partner with tech leaders and stakeholders to influence priorities and ensure long-term scalability and impact

• Stay engaged with the broader ML and Search research community applying emerging trends to Spotify’s challenges

Who You Are

• You have a strong background in machine learning and recommender systems bridging research and user impact

• You have hands-on experience training and operating transformer models in production or strong interest in doing so

• You have production experience developing large-scale ML systems in Java Scala Python or similar languages. Experience with PyTorch or TensorFlow is a strong plus

• You are comfortable navigating ambiguity and leading high-impact projects from start to finish

• You’re a systems thinker and strong communicator who can align and influence technical and product stakeholders

• You care deeply about agile processes data-driven development and reliability.You’re eager to apply emerging ML trends particularly in LLMs and generative recommenders to Spotify’s challenges

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.

The United States base range for this position is $215136- $307337 plus equity. The benefits available for this position include health insurance six month paid parental leave 401(k) retirement plan monthly meal allowance 23 paid days off 13 paid flexible holidays paid sick leave. These ranges may be modified in the future.