Machine Learning Engineer - Personalization

The Personalization team makes deciding what to play next easier and more enjoyable for every listener. From Daily Mix to Discover Weekly, we’re behind some of Spotify’s most-loved features. We built them by understanding the world of music and podcasts better than anyone else. Join us and you’ll keep millions of users listening by making great recommendations to each and every one of them.
We are looking for a Machine Learning Engineer with a future focus on reinforcement learning to join our team that is working on applying and experimenting with state of the art machine learning techniques for guiding every user to a satisfying listening experience every time. By leveraging both human and machine learning intelligence we empower content professionals to efficiently combine their expertise in technology and culture to help connect listeners to content and artists they’ll love. 
You will be working with a cross-functional team in Stockholm who’s driving the application of machine learning to make Spotify’s beloved playlists and strategic content promotion even better. As a machine learning engineer in the team, you will contribute and influence the direction within the team and work with multiple product and engineering stakeholders to power different personalization projects within the Programming Platform product area. 
Join us and you’ll keep millions of users listening to great recommendations every day. We’re a team of technologists, product insight specialists, designers, and product managers in Stockholm, Boston, New York, and London.

What You'll Do:

• Contribute to designing, building, evaluating, shipping, and refining Spotify’s personalization products by hands-on ML development
• Collaborate with a cross functional agile team spanning user research, design, data science, product management, and engineering to build new product features that advance our mission to connect artists and fans in personalized and relevant ways
• Prototype new approaches and productionize solutions at scale for our hundreds of millions of active users
• Drive optimization, testing, and tooling to improve quality
• Be part of an active group of machine learning practitioners across Spotify
• Work from our office in Stockholm

Who You Are:

• You have an MSc or PhD in Computer Science, Machine Learning, Engineering, Mathematics, Physics, or equivalent.
• You have a background in machine learning, enjoy applying theory to develop real-world applications, with experience and expertise in machine learning algorithms for recommender systems and/or computational advertising. 
• Familiarity or a hands-on experience with reinforcement learning approaches is a big plus. 
• You have hands-on experience implementing production machine learning systems at scale in Python, Scala, Java or similar languages. Previous industry experience with frameworks such as Tensorflow and the Tensorflow ecosystem (TFX) is also a big plus.
• You have experience with data pipeline tools like Apache Beam, Spark, etc., and cloud platforms like GCP or AWS
• You care and are able to execute on agile software processes, data-driven development, reliability, and disciplined experimentation
• You love your customers even more than your code

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 320 million users.