Scribd, Inc.
About the Company
At Scribd (pronounced “scribbed”), our mission is to spark human curiosity. Join our team as we create a world of stories and knowledge, democratize the exchange of ideas and information, and empower collective expertise through our four products: Everand, Scribd, Slideshare, and Fable. We support a culture where our employees can be real and bold; where we debate and commit as we embrace plot twists; and where every employee is empowered to take action as we prioritize the customer. Scribd Flex provides flexible work options, and occasional in-person attendance is required for all employees, regardless of location. We hire for “GRIT”: setting and achieving goals, delivering results, contributing innovative ideas, and positively influencing the team through collaboration and attitude. The Team
The ML Data Engineering team powers metadata extraction, enrichment, and content understanding across Scribd brands, processing hundreds of millions of documents and billions of images to enable content discovery and trust for millions of users. We work at the intersection of machine learning, data engineering, and distributed systems, deploying scalable ML and LLM-powered solutions in production.
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At Scribd (pronounced “scribbed”), our mission is to spark human curiosity. Join our team as we create a world of stories and knowledge, democratize the exchange of ideas and information, and empower collective expertise through our four products: Everand, Scribd, Slideshare, and Fable. We support a culture where our employees can be real and bold; where we debate and commit as we embrace plot twists; and where every employee is empowered to take action as we prioritize the customer. Scribd Flex provides flexible work options, and occasional in-person attendance is required for all employees, regardless of location. We hire for “GRIT”: setting and achieving goals, delivering results, contributing innovative ideas, and positively influencing the team through collaboration and attitude. The Team
The ML Data Engineering team powers metadata extraction, enrichment, and content understanding across Scribd brands, processing hundreds of millions of documents and billions of images to enable content discovery and trust for millions of users. We work at the intersection of machine learning, data engineering, and distributed systems, deploying scalable ML and LLM-powered solutions in production.
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