Machine Learning Engineering Manager - Surfaces Music

The Surfaces Music team builds the systems that power music recommendations across some of Spotify’s most visible experiences, including Home and the Now Playing view. We work across candidate generation, ranking, and embedding models to help listeners discover both new releases and deep catalog favorites.

We’re also shaping the next generation of personalization through transformer-based models that bring more dynamic, context-aware recommendations to millions of listeners. You’ll collaborate closely with teams across Personalization, Experience, and Music to evolve how discovery works across Spotify.

What You'll Do:
•
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

Who You Are:
•
You have 5+ years of experience in software engineering or machine learning, including 2+ years supporting or leading a team

•
You have experience working on recommendation systems, including ranking, retrieval, or embedding-based approaches

•
You understand how to build and operate machine learning systems in production at scale

•
You are familiar with modern machine learning approaches such as deep learning or large language models

•
You have worked with cross-functional partners to deliver complex projects with multiple dependencies

•
You care about building products that are measurable, impactful, and grounded in user needs

•
You are comfortable working with experimentation and using data to guide decisions

•
You create an environment where collaboration, trust, and inclusion are prioritized

•
You stay engaged with technical decisions and enjoy supporting engineers in solving complex problems

•
You are curious about how AI tools can improve engineering workflows and team effectiveness

Who You Are:
• This role is based in New York

• We offer you the flexibility to work where you work best! There will be some in person meetings, but still allows for flexibility to work from home.

The United States base range for this position is $164,448 - $234,926 plus equity. The benefits available for this position include 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. These ranges may be modified in the future.

Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what’s playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It’s in our differences that we will find the power to keep revolutionizing the way the world listens.

At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know - we’re here to support you in any way we can.

Spotify transformed music listening forever when we launched in 2008. Our mission is to unlock the potential of human creativity by giving a million creative artists the opportunity to live off their art and billions of fans the chance to enjoy and be passionate about these creators. Everything we do is driven by our love for music and podcasting. Today, we are the world’s most popular audio streaming subscription service.