Machine Learning Engineering Manager, Personalization
Spotify
Machine Learning Engineering Manager, Personalization
Job Description
The Personalization team makes deciding what to play next easier and more enjoyable for every listener. From DJ to Discover Weekly, we’re behind some of Spotify’s most-loved features. We built them by understanding the world of music and podcasts better than anyone else and by leveraging the latest in Generative AI. Join us and you’ll keep millions of users listening by giving great music and talk experiences to each and every one of them. We prefer that our team members be physically located in Eastern Standard/Daylight time zones for the purpose of our collaboration hours.
Personalization is looking for an ML Engineering Manager to help shape the future of how we give users more control of their experience, leveraging large language models (LLMs) and agentic workflows. This is an exciting mix of platform-level user understanding and experience level user presentation.
Locations
- New York, New York, United States
Salary
Salary details available upon request
Estimated Salary Rangemedium confidence
450,000 - 750,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- developing great peopleintermediate
- cultivating a strong engineering culture in an agile environmentintermediate
- developing production-scale, data-driven AI systemsintermediate
- people managementintermediate
- Generative AIintermediate
Required Qualifications
- You thrive when developing great people and phenomenal, meaningful products (experience)
- You have experience in cultivating a strong engineering culture in an agile environment (experience)
- You have previous experience developing production-scale, data-driven AI systems. Platform-level experience would be nice, too. (experience)
- You have experience in people management, with the humility to realize where you’re still growing (experience)
- You are excited but not overhyped by the potential of Generative AI (experience)
Preferred Qualifications
- Platform-level experience would be nice, too. (experience)
Responsibilities
- You will be accountable for the health of team of ML, Backend and Data Engineers, serving them through hiring, coaching, mentoring, and hands-on career development
- You will be accountable for team delivery, helping set goals that integrate both ambition and sustainability and proposing tradeoffs to optimize value delivered
- You will be accountable for the team’s technical strategy and architecture, working with the engineers in developing it. Similarly, you will be accountable for the health of the team’s systems.
- You will work with a product manager to ensure that the team is delivering products of value.
- You may give leadership to other efforts that fit your passion and Spotify’s needs in collaboration with other managers and engineers.
Benefits
- general: We offer you the flexibility to work where you work best! For this role, you can be within the EST time zone as long as we have a work location.
- general: This team operates within the Eastern Standard time zone for collaboration.
Tags & Categories
Machine Learning Engineering Manager, Personalization
Spotify
Machine Learning Engineering Manager, Personalization
Job Description
The Personalization team makes deciding what to play next easier and more enjoyable for every listener. From DJ to Discover Weekly, we’re behind some of Spotify’s most-loved features. We built them by understanding the world of music and podcasts better than anyone else and by leveraging the latest in Generative AI. Join us and you’ll keep millions of users listening by giving great music and talk experiences to each and every one of them. We prefer that our team members be physically located in Eastern Standard/Daylight time zones for the purpose of our collaboration hours.
Personalization is looking for an ML Engineering Manager to help shape the future of how we give users more control of their experience, leveraging large language models (LLMs) and agentic workflows. This is an exciting mix of platform-level user understanding and experience level user presentation.
Locations
- New York, New York, United States
Salary
Salary details available upon request
Estimated Salary Rangemedium confidence
450,000 - 750,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- developing great peopleintermediate
- cultivating a strong engineering culture in an agile environmentintermediate
- developing production-scale, data-driven AI systemsintermediate
- people managementintermediate
- Generative AIintermediate
Required Qualifications
- You thrive when developing great people and phenomenal, meaningful products (experience)
- You have experience in cultivating a strong engineering culture in an agile environment (experience)
- You have previous experience developing production-scale, data-driven AI systems. Platform-level experience would be nice, too. (experience)
- You have experience in people management, with the humility to realize where you’re still growing (experience)
- You are excited but not overhyped by the potential of Generative AI (experience)
Preferred Qualifications
- Platform-level experience would be nice, too. (experience)
Responsibilities
- You will be accountable for the health of team of ML, Backend and Data Engineers, serving them through hiring, coaching, mentoring, and hands-on career development
- You will be accountable for team delivery, helping set goals that integrate both ambition and sustainability and proposing tradeoffs to optimize value delivered
- You will be accountable for the team’s technical strategy and architecture, working with the engineers in developing it. Similarly, you will be accountable for the health of the team’s systems.
- You will work with a product manager to ensure that the team is delivering products of value.
- You may give leadership to other efforts that fit your passion and Spotify’s needs in collaboration with other managers and engineers.
Benefits
- general: We offer you the flexibility to work where you work best! For this role, you can be within the EST time zone as long as we have a work location.
- general: This team operates within the Eastern Standard time zone for collaboration.
Tags & Categories