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 Discover Weekly to AI DJ, we’re behind some of Spotify’s most-loved features. We built them by understanding the world of music, podcasts, and listeners better than anyone else. Join us and you’ll keep millions of users listening by making great recommendations to each and every one of them.
The Next Generation Sessions (NextGen) product area within Personalization is evolving listening beyond playlists, inventing new personalized listening (and watching!) sessions such as AI DJ, AI Playlist, Blend, Podcast Discovery Feed, and Music Discovery Feed. NextGen is a team of about 100 engineers, scientists, product managers, and music and voice domain experts working remotely and in offices in New York, Boston, London, and Stockholm.
This ML Engineering Manager role will provide technical leadership to a newly formed squad of ~12 engineers focusing on exciting new AI-driven music session experiences. In collaboration with a cross-functional and cross-team leadership group, you will drive expansion of NextGen's AI experiences in music, leveraging the success of AI DJ and AI Playlist, advancing and spearheading the development of entirely new music recommendations experiences and capabilities.
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
- MLintermediate
- backendintermediate
- data engineersintermediate
- generative AIintermediate
- agent frameworksintermediate
- AI-assisted codingintermediate
- modern ML theory and practicesintermediate
- architectural visionintermediate
- ML modelingintermediate
- codingintermediate
Required Qualifications
- Experienced leading delivery of consumer-facing ML products at scale (experience)
- Energized by rapid change, ambiguity, and opportunity, with a proven track record transforming innovative ideas into impactful products (experience)
- Skilled with current generative AI and agent technologies (experience)
- Actively using AI-assisted coding and product development tools to prototype new products (experience)
- Expert in modern ML theory, practices, and their practical implementation (experience)
- Comfortable providing detailed technical direction and resolving complex engineering challenges (experience)
- Collaborative and influential, thriving in strategic discussions with senior engineers and managers (experience)
- Focused on user outcomes, rigorously grounding decisions in user data and insights (experience)
- Experienced in nurturing technical talent, committed to growing engineers' skills in technology and leadership (experience)
Responsibilities
- Lead a talented team of ML, backend, and data engineers to build and launch innovative AI-driven personalized music experiences
- Debate and align technical strategies with senior engineering leaders and partner teams, translate these strategies clearly back to your squad, and actively guide architectural vision and day-to-day ML modeling and coding decisions
- Bring external experience in generative AI and agent frameworks to enhance Spotify's personalized music sessions
- Navigate ambiguity, driving innovation through rapid prototyping and iterative development in cross-functional teams
- Champion AI-assisted coding practices, continually expanding the team's technical capabilities
- Foster strong research partnerships to scale innovative solutions from experimentation to production
- Develop and grow your team's talent through hiring, coaching, mentoring, and fostering a collaborative, adaptive culture
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. The squad is based in New York City.
- 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 Discover Weekly to AI DJ, we’re behind some of Spotify’s most-loved features. We built them by understanding the world of music, podcasts, and listeners better than anyone else. Join us and you’ll keep millions of users listening by making great recommendations to each and every one of them.
The Next Generation Sessions (NextGen) product area within Personalization is evolving listening beyond playlists, inventing new personalized listening (and watching!) sessions such as AI DJ, AI Playlist, Blend, Podcast Discovery Feed, and Music Discovery Feed. NextGen is a team of about 100 engineers, scientists, product managers, and music and voice domain experts working remotely and in offices in New York, Boston, London, and Stockholm.
This ML Engineering Manager role will provide technical leadership to a newly formed squad of ~12 engineers focusing on exciting new AI-driven music session experiences. In collaboration with a cross-functional and cross-team leadership group, you will drive expansion of NextGen's AI experiences in music, leveraging the success of AI DJ and AI Playlist, advancing and spearheading the development of entirely new music recommendations experiences and capabilities.
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
- MLintermediate
- backendintermediate
- data engineersintermediate
- generative AIintermediate
- agent frameworksintermediate
- AI-assisted codingintermediate
- modern ML theory and practicesintermediate
- architectural visionintermediate
- ML modelingintermediate
- codingintermediate
Required Qualifications
- Experienced leading delivery of consumer-facing ML products at scale (experience)
- Energized by rapid change, ambiguity, and opportunity, with a proven track record transforming innovative ideas into impactful products (experience)
- Skilled with current generative AI and agent technologies (experience)
- Actively using AI-assisted coding and product development tools to prototype new products (experience)
- Expert in modern ML theory, practices, and their practical implementation (experience)
- Comfortable providing detailed technical direction and resolving complex engineering challenges (experience)
- Collaborative and influential, thriving in strategic discussions with senior engineers and managers (experience)
- Focused on user outcomes, rigorously grounding decisions in user data and insights (experience)
- Experienced in nurturing technical talent, committed to growing engineers' skills in technology and leadership (experience)
Responsibilities
- Lead a talented team of ML, backend, and data engineers to build and launch innovative AI-driven personalized music experiences
- Debate and align technical strategies with senior engineering leaders and partner teams, translate these strategies clearly back to your squad, and actively guide architectural vision and day-to-day ML modeling and coding decisions
- Bring external experience in generative AI and agent frameworks to enhance Spotify's personalized music sessions
- Navigate ambiguity, driving innovation through rapid prototyping and iterative development in cross-functional teams
- Champion AI-assisted coding practices, continually expanding the team's technical capabilities
- Foster strong research partnerships to scale innovative solutions from experimentation to production
- Develop and grow your team's talent through hiring, coaching, mentoring, and fostering a collaborative, adaptive culture
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. The squad is based in New York City.
- general: This team operates within the Eastern Standard time zone for collaboration.
Tags & Categories