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.

Location

New York

Job type

Permanent

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

For this role you should be based in New York City (USA).

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Our global benefits

Extensive learning opportunities, through our dedicated team, GreenHouse.

Flexible share incentives letting you choose how you share in our success.

Global parental leave, six months off - fully paid - for all new parents.

All The Feels, our employee assistance program and self-care hub.

Flexible public holidays, swap days off according to your values and beliefs.

Learn about life at Spotify

The United States base range for this position is $136,878 - $195,540 plus equity. The benefits available for this position include health insurance, six month paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, 13 paid flexible holidays, paid sick leave. These ranges may be modified in the future.