Staff Machine Learning Engineer, Content and Catalog Management - Spotify
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.
The Content and Catalog Management (CoCaM) team works at the heart of the Content Platform R&D studio, the central point for the ingestion, distribution, management, knowledge and growth of all content you experience through Spotify products. In CoCaM, we drive the management of content and make decisions that impact the whole of Spotify on all contents appropriateness, availability, quality and accuracy. Through reactive and proactive reporting mechanisms we use the knowledge of Content Platform and apply platform & business policy with content, user, financial and experiential context to make and store a decision best for Creators, Consumers and Spotify.
We are seeking a Machine Learning (ML) Staff Engineer eager to own the definition, adoption and expansion of ML usage within our content and catalogue management platform. You’ll work with a community of engineers, researchers, product managers, designers and data scientists with varied levels of exposure and experience in ML. Together with the CoCaM Engineering Lead, Content Platform Engineering Leadership and fellow Staff Engineers; you’ll own the expansion of CoCaM ML knowledge and expertise, and collaborate to find opportunities for more efficient, effective and consistent use of ML in our decision-making pipeline.
Last updated: 4 hours ago
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