Senior Machine Learning Engineer - Lifetime Value

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 Senior Machine Learning Engineer (MLE) to join our Life Time Value (LTV) product area of hardworking engineers that are passionate about understanding what drives  users’ long term satisfaction with Spotify, and how our content affects that. As an integral part of the squad, you will collaborate with research scientists, data scientists and other engineers in prototyping and productizing state-of-the-art ML and causal inference techniques for content value understanding, thus advancing our knowledge of Spotify’s content.

What You'll Do

• Prototype new ML approaches for content value understanding and productionize solutions at scale for our hundreds of millions of active users
• Collaborate with a multi-functional agile team spanning user research, data science, product management, and engineering to build new product features that inform and enrich Spotify’s content catalogue
• Promote and role-model best practices of ML model development, testing, evaluation, etc., both inside the team as well as throughout the organization
• Be part of an active group of machine learning practitioners in New York (and across Spotify) collaborating with one another

Who You Are

• You have a strong background in machine learning, enjoy applying theory to develop real-world applications, with expertise in personalized machine learning algorithms. Experience with causal inference methodologies is a strong plus
• You have hands-on experience implementing production machine learning systems at scale in Scala, Python, Java, or similar languages. Experience with tools like TensorFlow, Scikit-learn, CausalML, EconML 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 care about agile software processes, modular code design following best practices, and disciplined experimentation with focus on repeatability
• 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.