Machine Learning Engineer II, Content Understanding

As Spotify grows its video catalog, understanding and classifying visual content in our catalog becomes very important to support moderation, search and recommendation use cases. We are a small, cross-functional team of Machine Learning Engineers and Data Engineers leveraging state of the art machine learning solely focused on building and deploying visual understanding models. 
Delivering the best Spotify experience possible. To as many people as possible. In as many moments as possible. That’s what the Experience team is all about. We use our deep understanding of consumer expectations to enrich the lives of millions of our users all over the world, bringing the music and audio they love to the devices, apps and platforms they use every day. Know what our users want? Join us and help Spotify give it to them.
As a Machine Learning Engineer in our Content Understanding teams, you will help define and build ML deployed at scale in support of a broad range of use cases driving value in media and catalog understanding.

What You'll Do

• Build production systems that enrich and improve our listeners’ experience on the platform
• Contribute to designing, building, evaluating, shipping, and refining Spotify’s product by hands-on ML development
• Prototype new approaches and production-ize solutions at scale for our hundreds of millions of active users
• Help drive optimization, testing, and tooling to improve quality
• Perform data analysis to establish baselines and inform product decisions
• Collaborate with a cross functional agile team spanning design, data science, product management, and engineering to build new technologies and features

Who You Are

• You have professional experience in applied machine learning
• Extensive experience working in a product and data-driven environment (Python, Scala, Java, SQL, or C++, with Python experience required) and cloud platforms (GCP or AWS)
• You have some hands-on experience implementing or prototyping machine learning systems at scale 
• You have experience architecting data pipelines and are self-sufficient in getting the data you need to build and evaluate models, using tools like Dataflow, Apache Beam, or Spark
• You care about agile software processes, data-driven development, reliability, and disciplined experimentation
• You have experience and passion for fostering collaborative teamsExperience with TensorFlow, pyTorch, and/or Google Cloud Platform is a plus
• Experience with building data pipelines and getting the data you need to build and evaluate your models, using tools like Apache Beam / Spark is a plus

Where You'll Be

• You will work out of our London office