ML Engineering Manager, Personalization - Lead at Scale

Spotify; New York (NY); On-site; USD 184,000 - 263,000; Full time

Benefits offered by this job

Health insurance

Six months parental leave

401(k) retirement plan

Monthly meal allowance

23 paid days off

13 paid flexible holidays

Paid sick leave

Job summary

Spotify is seeking an Engineering Manager to lead the Saturn squad within Sessions in the Personalization organization. You will guide a team of ML, backend, and data engineers, shaping the future of personalized listening experiences through advanced ML capabilities.

The role focuses on training and refining models that rank and personalize features like Radio and Daily Mix, while exploring generative AI approaches and large language models to deliver meaningful user value across millions of

Qualifications

• Experience leading and developing high-performing engineering teams.
• Deep expertise building and operating production ML systems at scale.
• Understanding the end-to-end ML lifecycle from experimentation to deployment and monitoring.
• Experience with large language models and generative AI applications.

Responsibilities

• Lead, coach, and develop a team of ML engineers and data engineers.
• Set technical direction and partner with Product, Data Science, and Engineering leaders.
• Guide design, deployment, and operation of production ML systems at scale.
• Mentor engineers, manage performance, and provide feedback.
• Drive execution by prioritizing work and removing obstacles.
• Promote engineering excellence with modern software practices.

Skills

Leadership

Team coaching

ML engineering

Production ML systems

LLMs / Generative AI

Cross-functional collaboration

Communication

Tools

ML frameworks

Job description

Spotify is seeking an Engineering Manager to lead the Saturn squad within Sessions in the Personalization organization. You will guide a team of ML, backend, and data engineers, shaping the future of personalized listening experiences through advanced ML capabilities.

The role focuses on training and refining models that rank and personalize features like Radio and Daily Mix, while exploring generative AI approaches and large language models to deliver meaningful user value across millions of