About the job
About Scribd:
At Scribd Inc. (pronounced “scribbed”), we are driven by a mission to ignite human curiosity. Join our innovative team as we cultivate a universe of stories and knowledge, democratize the sharing of ideas and information, and empower collective expertise through our diverse products: Everand, Scribd, Slideshare, and Fable.
This position is an officially approved, open role within our organization.
We foster a culture where authenticity and boldness thrive; where discussions lead to commitment as we embrace unexpected challenges; and where every team member is empowered to take initiative with a steadfast focus on our customers.
Our workplace structure emphasizes a balance between individual flexibility and community engagement. Through our flexible work initiative, Scribd Flex, employees can collaborate with their managers to design a work style that best suits their needs. Our approach prioritizes intentional in-person moments to strengthen collaboration, culture, and connection. Therefore, occasional in-person attendance is a requirement for all Scribd Inc. employees, regardless of their location.
What do we seek in our new team members? We value “GRIT.” The essence of GRIT is the blend of passion and perseverance towards achieving long-term goals. At Scribd Inc., we believe in the immense potential this can unlock and encourage our employees to adopt a GRIT-driven approach to their work. In practical terms, GRIT also serves as an acronym that highlights the standards we uphold: we are searching for candidates who can set and achieve Goals, deliver Results in their responsibilities, contribute Innovative solutions, and positively impact the broader Team through collaboration and attitude.
About the Team:
The ML Data Engineering team is at the forefront of metadata extraction, enrichment, and content understanding across all Scribd brands. Our team processes hundreds of millions of documents and billions of images, providing high-quality metadata that enhances content discovery and trust for millions of users globally.
Operating at scale, our systems manage diverse datasets including user-generated content (UGC), ebooks, audiobooks, and more. We work at the intersection of machine learning, data engineering, and distributed systems, closely collaborating with applied research and product teams to deploy scalable machine learning solutions.
