Description
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.
Here are some examples of the work you may support: Audio fingerprinting to understand what music is played in podcasts enabling musicians to get royalties, Video and image tagging to understand what is happening in any video on Spotify for moderation and recommendations, Audiobook Author attribution using graph ML approaches for search and recommendations, Categorizing tracks in the catalog to know which are functional content or music tracks leveraged in royalty calculations and in search and recommendations.
Our teams are composed of product, machine learning, data and backend engineers, and subject matter experts who average 11 years behind the scenes in the music industry.
We are looking for a Machine Learning Engineer to help us define and build Spotify’s capabilities in this area. Our team expands the state of the art in AI-based machine technology, which enables intelligent, efficient, and intuitive ways to search, re-use, explore or process metadata. You will use world-class engineering and machine learning techniques on real-world, internal, and external big data to directly impact the evolution of our music catalog.
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 teams
- Experience 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
- This role is based in London (UK).
- We offer you the flexibility to work where you work best! There will be some in person meetings, but still allows for flexibility to work from home. We ask that you come in 3 times per week.
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