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.
Have you ever had a debate at a party about who originally wrote a song versus who covered it? Tried to find a sample you loved more than the song you heard it in? Wondered who was actually in the recording booth for your favorite song (on both sides of the glass)? Wonder what Britney Spears, Nsync, Pink, Katy Perry, Taylor Swift, and The Weeknd all have in common? (The same songwriter wrote Billboard number-one singles for all of them). Who gets paid every time we sing "Happy Birthday"?
Music attribution at scale is one of the great unsolved technical problems of the music industry, and we're building cutting-edge technology to solve it. Our goal is to solve this problem for the more than 60 million music tracks playable on Spotify, building a knowledge graph through cutting-edge machine learning models, deep subject matter expertise, and close integration with human-in-the-loop processes across Spotify and the industry. Content Platform's catalog data powers Spotify experiences from Artist pages in the app, search and recommendations, human playlist curation, Spotify for Artists, and our music industry strategy.
Our teams are composed of product, machine learning, data and backend engineers, and subject matter experts who average 11 years behind the scenes in the music industry.
We are looking for a Machine Learning Engineering Manager to help us lead teams in support of Spotify's Music Knowledge Graph. Our team employs 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 you'll do
Who you are
- Coordinate with Product and Engineering leadership to identify both the long-term and short-term needs of the knowledge graph.
- Lead the team in building and deploying robust ML/DL models that improve entity extraction, classification, resolution, and disambiguation within the Music Knowledge Graph across multiple languages (e.g. English, Korean, etc.), time dimensions, and territories.
- 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.
Where you'll be
- 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 have expertise 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 have experience in cultivating a strong engineering culture in an agile environment.
- 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 Americas region in which we have a work location and is within working hours.
- Working hours? We operate within the Eastern Standard time zone for collaboration and ask that all be located in 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.
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.Global COVID and Vaccination Disclosure
Spotify is committed to safety and well-being of our employees, vendors and clients. We are following regional guidelines mandating vaccination and testing requirements, including those requiring vaccinations and testing for in-person roles and event attendance. For the US, we have mandated that all employees and contractors be fully vaccinated in order to work in our offices and externally with any third-parties. For all other locations, we strongly encourage our employees to get vaccinated and also follow local COVID and safety protocols.