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.LocationsNew YorkJob TypePermanentDelivering 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 DoBuild production systems that enrich and improve our listeners’ experience on the platformContribute to designing, building, evaluating, shipping, and refining Spotify’s product by hands-on ML developmentPrototype new approaches and production-ize solutions at scale for our hundreds of millions of active usersHelp drive optimization, testing, and tooling to improve qualityPerform data analysis to establish baselines and inform product decisionsCollaborate with a cross-functional agile team spanning design, data science, product management, and engineering to build new technologies and featuresWho You AreYou have professional experience in applied machine learningExtensive 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 scaleYou 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 SparkYou care about agile software processes, data-driven development, reliability, and disciplined experimentationYou have experience and passion for fostering collaborative teams. Experience with TensorFlow, PyTorch, and/or Google Cloud Platform is a plusExperience with building data pipelines and getting the data you need to build and evaluate your models, using tools like Apache Beam/Spark is a plusWhere You'll BeWe are a distributed workforce enabling our band members to find a work mode that is best for them!Where in the world? For this role, it can be within the Americas region in which we have a work locationPrefer an office to work from home instead? Not a problem! We have plenty of options for your working preferences.Working hours? We operate within the Eastern Standard time zone for collaborationBenefitsExtensive 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.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.

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