Senior Machine Learning Engineer, Personalization

The Personalization team makes deciding what to play next easier and more enjoyable for every listener. From Blend 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 ask that our team members be physically located in Central European time or Eastern Standard/Daylight time zones for the purposes of our collaboration hours.
Home is the default screen in the Spotify apps, and over 50M users use it every day. It surfaces the best of what Spotify has to offer, including music, podcasts and a host of new formats for every situation, personalized playlists, new releases, old favorites, and undiscovered gems. We believe that personalizing Home improves the happiness of our users, and that this satisfaction directly impacts the success of Spotify.
The Home Product Area consists of multiple teams passionate about making the Home screen of Spotify a completely personalized experience, through a combination of our broad content catalog, machine learning-based ranking and candidate generation, and creative user experience features. Our mission is to make Home reflect the individual tastes, habits and preferences of our listeners and help them connect with the content they love faster and easier.
We, at Home, are looking for a hard-working Machine Learning Engineer to join our Music Recommendation team and help us grow and expand our music recommendation and be ever more reactive to our listeners’ preferences, habits and interests by giving them the right content at the right time.

What You'll Do

• Chip in to crafting, building, evaluating, shipping, and refining Spotify’s personalization products by hands-on ML development
• Lead research into music recommender systems and other areas relevant to building a personalized experience on Home
• Prototype innovative approaches and productionize solutions at scale for our hundreds of millions of active users
• Define and implement standard methodologies for building and evaluating machine learning models
• Collaborate with a multi-functional agile team spanning machine learning, product management, and backend and data engineering to build new product features that advance our mission to connect artists and fans in personalized and relevant ways
• Promote and role-model standard processes of ML systems development, testing, evaluation, etc., both inside the team as well as throughout the organization

Who You Are

• You have a strong background in machine learning, enjoy applying theory to develop real-world applications, with experience and expertise in personalized machine learning algorithms, especially recommender systems
• You understand the architecture and development workflow for large-scale batch and streaming machine-learning systems
• You are comfortable writing SQL queries, exploring data, and developing good hypotheses for product improvements
• You are comfortable and have experience researching new and novel ways to solve problems through machine learning and help us advance our existing methodologies
• You have hands-on experience implementing production machine learning systems at scale in Java, Scala, Python, or similar languages. Experience with TensorFlow, PyTorch, Scikit-learn, XGBoost, etc is a strong plus
• You have experience with large scale, distributed data processing frameworks/tools like Apache Beam, Apache Spark, or even our open source API for it, Scio and cloud platforms like GCP or AWS
• You love your customers even more than your code

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 or European regions in which we have a work location and is within working hours
• Working hours? We operate between the Eastern and Central European time zones for collaboration
• 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 DisclosureSpotify 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.