Spotify AB
Machine Learning Engineer
Personalization
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, podcasts, and audiobooks better than anyone else so that we can make great recommendations to every individual person and keep the world listening. Every day, hundreds of millions of people all over the world use the products we build, including destinations like Home and Search, as well as original playlists such as Discover Weekly and Daily Mix. Location New York Job type Permanent About Hulk Hulk stands for Human Understandable Language Knowledge. The team owns critical assets that power recommendation and distribution across Spotify. We are part of the LLM Foundations Product Area, heavily using modern AI techniques and LLMs to derive content understanding and establish reliable, scalable systems for sharing knowledge across Spotify teams. What You'll Do Lead technical initiatives within your team and across Spotify Coordinate projects across teams within Spotify Collaborate with engineers, product owners, and designers to solve challenging problems for global media delivery Contribute as a member of an autonomous, cross-functional agile team Architect, design, develop, and deploy ML models for podcast recommendations across various surfaces Lead in Homes ML community and work within existing platforms and systems Who You Are Experienced in technical leadership or mentorship Strong background in machine learning, especially recommender systems Experience designing and building ML systems at Spotify, including spotify-kubeflow and salem Proficient in feature engineering and building scalable data pipelines in Scio Deep understanding of ML systems and infrastructure Experience with TensorFlow or PyTorch; familiarity with Kubeflow, Ray is a plus Where You'll Be Flexible work location within North America, aligned with the Eastern Standard Time zone for collaboration Additional benefits include extensive learning opportunities, share incentives, parental leave, employee assistance programs, flexible holidays, and competitive compensation with health benefits, retirement plans, and paid time off. Spotify is an equal opportunity employer committed to diversity and inclusion. We support accommodations throughout the hiring process. Join us to help revolutionize the way the world listens. #J-18808-Ljbffr
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, podcasts, and audiobooks better than anyone else so that we can make great recommendations to every individual person and keep the world listening. Every day, hundreds of millions of people all over the world use the products we build, including destinations like Home and Search, as well as original playlists such as Discover Weekly and Daily Mix. Location New York Job type Permanent About Hulk Hulk stands for Human Understandable Language Knowledge. The team owns critical assets that power recommendation and distribution across Spotify. We are part of the LLM Foundations Product Area, heavily using modern AI techniques and LLMs to derive content understanding and establish reliable, scalable systems for sharing knowledge across Spotify teams. What You'll Do Lead technical initiatives within your team and across Spotify Coordinate projects across teams within Spotify Collaborate with engineers, product owners, and designers to solve challenging problems for global media delivery Contribute as a member of an autonomous, cross-functional agile team Architect, design, develop, and deploy ML models for podcast recommendations across various surfaces Lead in Homes ML community and work within existing platforms and systems Who You Are Experienced in technical leadership or mentorship Strong background in machine learning, especially recommender systems Experience designing and building ML systems at Spotify, including spotify-kubeflow and salem Proficient in feature engineering and building scalable data pipelines in Scio Deep understanding of ML systems and infrastructure Experience with TensorFlow or PyTorch; familiarity with Kubeflow, Ray is a plus Where You'll Be Flexible work location within North America, aligned with the Eastern Standard Time zone for collaboration Additional benefits include extensive learning opportunities, share incentives, parental leave, employee assistance programs, flexible holidays, and competitive compensation with health benefits, retirement plans, and paid time off. Spotify is an equal opportunity employer committed to diversity and inclusion. We support accommodations throughout the hiring process. Join us to help revolutionize the way the world listens. #J-18808-Ljbffr