Delivering the best Spotify experience possible. To as many people as possible. In as many moments as possible. That’s what the Experience team is all about. We use our deep understanding of consumer expectations to enrich the lives of millions of our users all over the world, bringing the music and audio they love to the devices, apps and platforms they use every day. Know what our users want? Join us and help Spotify give it to them.

We are looking for a Machine Learning Engineering Manager to help us lead teams in support of Spotify’s Content Understanding teams. Our teams employ state of the art in AI-based machine technology, which enables intelligent, efficient, and intuitive ways to search, re-use, explore or process metadata. Engineers will use world-class engineering and machine learning techniques on real-world, internal, and external big data to directly impact the evolution of our music catalog.

What Youll Do

Coordinate with Product and Engineering leadership to identify both the long-term and short-term needs of the knowledge graph.
Contribute to our team-wide product ideation in collaboration with other engineering leaders, engineers, researchers, product managers, and subject-matter experts on the team.
Communicate complex concepts and the results of analyses in a clear and effective manner to technical and non-technical audiences.
Collaborate with other team members and cross-functionally to share knowledge and discuss initiatives.

Who You Are

You can draw on substantial depth and breadth of management experience to lead and grow a machine learning team.
You collaborate well with teams with different backgrounds/expertise/functions.
You have expertise in full product lifecycle; technical designs, project planning, iterative implementation, and successful product launches.
You care about data-driven development, reliability, and responsible experimentation.
You understand the application of intermediate principles of data science (machine learning, statistics, computer science, mathematics) to solve technical problems.
You are an expect in the ML Operations lifecycle; data acquisition, model training, and model deployment.
You love your customers even more than your code.
You have experience and passion for mentoring and encouraging collaborative teams.
You are experienced in cultivating a strong engineering culture in an agile environment.

Where Youll Be

We are a distributed workforce enabling our band members to find a work mode that is best for them!
Where in the world? For this role, it can be within the Eastern US region in which we have a work location and is within working hours.
Working hours? We operate within the Eastern US time zones for collaboration and ask that all be able to work within that time zone.
Prefer an office to work from home instead? Not a problem! We have plenty of options for your working preferences. Find more information about our Work From Anywhere options here.

The United States base range for this position is $172,000 - $246,000, plus equity. The benefits available for this position include health insurance, six month paid parental leave, 401(K) retirement plan, 23 paid days off, 13 paid flexible holidays, paid sick leave.

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.

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.