Job Description

Machine Learning
The User Platform (UP) studio is looking for our first Machine Learning Engineer to help us get better at accomplishing our mission: Connect Users with Spotify and Spotify with its Users.
Locations


London
Stockholm
Job type


Permanent


UP is a studio in the SAFE Alliance as part of Spotify's Platform Mission. The studio owns capabilities and infrastructure for Customer Identity and Access Management at Spotify directly providing 700M+ users across the world access to the audio experience they desire. The studio was formed in order to 1) provide a secure platform that helps users establish their identity and manage their account data on different surfaces; 2) Enable teams around Spotify to customize the overall offering given to users in a reliable manner.


As a part of the studio, you'll be part of bootstrapping the studio's ML capabilities focused on gaining confidence in who the user is - allowing us to provide our users with an offering that's relevant to them while ensuring the safety of our users. This would include solving (but not be limited to) things like assessing the age of a user etc.
What You'll Do

Lead the Design, development, evaluation and iteration of the necessary ML models. Collaborate with a multi-functional team spanning user research, design, data science, product management, and engineering to build new product features that advance Spotify's mission to deliver creativity to the world - one note, one voice, one idea at a time. Prototype new approaches and productionise solutions at scale for our hundreds of millions of active users Help drive optimisation, testing, and tooling to improve quality Help cross skill our engineering team with the machine learning craft. Be part of an active group of machine learning practitioners in your mission and across Spotify.
Who You Are

You have at least 6 years of experience working with ML models at scale. You have a strong background in machine learning, theory, and practice You are comfortable explaining the intuition and assumptions behind ML concepts You have hands-on experience implementing and maintaining production ML systems in Python, Scala, or similar languages Experience with TensorFlow is also a plus You are experienced with building data pipelines, and you are self-sufficient in getting the data you need to build and evaluate your models. You can pick up new skills to unblock yourself and maximise the impact you deliver. You preferably have experience with cloud platforms like GCP or AWS You care about agile software processes, data development, reliability, and focused experimentation You have a desire to drive business impact
Where You'll Be

This role is based London, United Kingdom or Stockholm, Sweden 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
Our global benefits


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 - 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.
Learn about life at Spotify


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 with a community of more than 500 million users.


Learn more about our culture