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.
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:
- 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.
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 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.
Where you'll 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 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.
What is Spotify’s workplace culture like in general?
It doesn’t matter who you are, where you come from or what music you love, at Spotify, you’ll be part of a brand that’s reimagining the entertainment industry. Our open collaborative environment and innovative, audacious brand gives you the opportunity to grow, have fun and do your best work. For an inside look at Spotify’s culture, check out our band manifesto
. What are some of the benefits you offer?
There are benefits to being in our band, and we’re not just talking about free Spotify Premium. Our rewards reflect our inclusive values and are extended to every band member, regardless of location or seniority. ● Extensive learning opportunities, through our dedicated team, GreenHouse. ● Flexible share incentives letting you choose how you share in our success. ● Global parental leave, six months off - fully paid - for all new parents. ● All The Feels, our employee assistance program and self-care hub. ● Flexible public holidays, swap days off according to your values and beliefs. ● Spotify On Tour, join your colleagues on trips to industry festivals and events What is Spotify’s approach to work-life balance?
Some of us work better in the office. Some of us are more productive at home. And many of us find we’re most effective when we have options. Here at Spotify, we don’t just recognize that one-desk-doesn’t-fit-all. We celebrate it with a Work From Anywhere Program that allows you to do just that. We believe we’re happier and more productive when we have the freedom to choose where we work. It helps us find better ways to communicate and collaborate with one another. It means we can work with the very best people for the job, regardless of what city or country they call home. It helps us to become a more diverse place to work, a place that can flex with our people as their lives and ambitions change. And perhaps best of all, it supports a better work-life balance. A life-work balance.