Spotify is looking for a Machine Learning Engineer to join our Creator Studio engineering organization. In Creator Studio, we build consumer and industry-facing products which provide creators new avenues for promoting their work, reaching new audiences, and deepening their connections with fans. If you're interested in building out the next revolution in the music industry and helping artists succeed in their careers, come join us!

As an ML Engineer on this team, you will tackle complex data problems surrounding audience segmentation, targeting, forecasting, and reporting. You will build data-driven solutions to bring promotional music experiences to our 350+ million active users on behalf of millions of artists. You will work with some of the most diverse datasets available -- user behaviors, acoustical analysis, revenue streams, cultural and contextual data, and other signals across our broad range of mobile and connected platforms. Above all, your work will impact the way the world experiences music and the way creators connect to their fans!

What you’ll do

• Contribute to designing, building, evaluating, shipping, and refining Spotify’s promotional products by hands-on ML development
• Collaborate with a multi-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

Who you are

• 3+ years of demonstrated ability in a similar engineering role or PhD in STEM with at least 1+ year of working experience in a technical role
• You have a strong background in data science and machine learning, with experience and expertise in designing, building, and testing models
• You have hands-on experience implementing production machine learning systems at scale in Java, Scala, Python, or similar languages. Experience with TensorFlow (or similar libraries such as PyTorch or Theano) is a plus.
• You preferably have experience with data pipeline tools like Apache Beam or even our open-source API for it, Scio and cloud platforms like GCP or AWS
• You care about agile software processes, data-driven development, reliability, and responsible experimentation.
• You understand the value of collaboration within teams.
• Experience in auction design, research, or modeling a plus

Where you'll be

• We are a distributed workforce enabling our band members to find a work mode best for them!
• Where in the world? For this role, it can be within the Americas region in which we have a work location
• 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.
• Working hours? We operate within the Eastern Standard time zone for collaboration.

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 with a community of more than 345 million users.