Machine Learning Engineering Manager – Surfaces Music
Spotify
full-time
Posted on:
Location Type: Remote
Location: New York • United States
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Salary
💰 $164,448 - $234,926 per year
About the role
- Lead and support a team of Backend, Data, and Machine Learning Engineers building recommendation systems used by hundreds of millions of listeners
- Set the technical direction for recommendation models across surfaces like Home and Now Playing
- Guide the development of candidate generation, ranking, and embedding systems that improve music discovery
- Partner with ML platform and infrastructure teams to evolve and scale generative recommendation models
- Work closely with Product, Data Science, and Design to define success metrics and turn insights into meaningful product improvements
- Ensure systems are reliable, efficient, and able to operate at global scale with low latency
- Support strong engineering practices across experimentation, model evaluation, and production monitoring
- Stay close to the technical work by reviewing architecture decisions and contributing to key discussions
- Encourage thoughtful adoption of AI-assisted development tools to improve team productivity and reduce repetitive work
- Create an inclusive, supportive team environment where engineers can grow and do their best work
- Collaborate with peers across the organization to align on shared goals and technical direction
Requirements
- 5+ years of experience in software engineering or machine learning, including 2+ years supporting or leading a team
- experience working on recommendation systems, including ranking, retrieval, or embedding-based approaches
- understanding of how to build and operate machine learning systems in production at scale
- familiarity with modern machine learning approaches such as deep learning or large language models
- experience with cross-functional partners to deliver complex projects with multiple dependencies
- care about building products that are measurable, impactful, and grounded in user needs
- comfortable working with experimentation and using data to guide decisions
- create an environment where collaboration, trust, and inclusion are prioritized
- stay engaged with technical decisions and enjoy supporting engineers in solving complex problems
- curious about how AI tools can improve engineering workflows and team effectiveness
Benefits
- health insurance
- six month paid parental leave
- 401(k) retirement plan
- monthly meal allowance
- 23 paid days off
- 13 paid flexible holidays
- paid sick leave
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
software engineeringmachine learningrecommendation systemsranking systemsretrieval systemsembedding systemsdeep learninglarge language modelsproduction monitoringAI-assisted development tools
Soft Skills
team leadershipcollaborationtrustinclusionproblem-solvingcommunicationsupportive environmentcuriositydata-driven decision makingengineering practices