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Machine Learning Engineering Manager, Personalization
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Job Description
What You'll Do
- 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
Who You Are
- Experienced leading delivery of consumer-facing ML products at scale
- Energized by rapid change, ambiguity, and opportunity, with a proven track record transforming innovative ideas into impactful products
- Skilled with current generative AI and agent technologies
- Actively using AI-assisted coding and product development tools to prototype new products
- Expert in modern ML theory, practices, and their practical implementation
- Comfortable providing detailed technical direction and resolving complex engineering challenges
- Collaborative and influential, thriving in strategic discussions with senior engineers and managers
- Focused on user outcomes, rigorously grounding decisions in user data and insights
- Experienced in nurturing technical talent, committed to growing engineers' skills in technology and leadership
Where You'll Be
- 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.
- This team operates within the Eastern Standard time zone for collaboration.
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