About the job
At Scribd, Inc., we aim to enhance human understanding. Our innovative products—Scribd®, Slideshare®, Everand™, and Fable—empower billions globally to not just access knowledge, but also to apply it and achieve expertise.
Company Culture
We foster an environment where our employees can be authentic and courageous, engaging in constructive debates while embracing unexpected challenges. Every team member is encouraged to take initiative, prioritizing customer needs.
We understand that optimal performance arises from a mix of personal flexibility and meaningful community interaction. Our Scribd Flex program allows team members to choose their working style and location, while still emphasizing in-person collaborations that enrich our culture. Attendance at occasional in-person events is necessary for all employees, regardless of their location.
We seek team members who embody “GRIT”—a blend of passion and perseverance towards long-term objectives. This ethos informs our approach to setting and achieving Goals, delivering impactful Results, fostering Innovation, and enhancing our Team dynamics through collaboration.
This posting represents an open position within our organization.
About Our Team:
Our ML Data Engineering team is responsible for metadata extraction, enrichment, and content comprehension across all Scribd offerings. We handle hundreds of millions of documents and billions of images, providing high-quality metadata to facilitate content discovery and trust for millions of users worldwide.
Operating at a massive scale, our systems support diverse datasets, including user-generated content (UGC), ebooks, audiobooks, and more. We collaborate closely with applied research and product teams to deploy scalable machine learning and large language model (LLM)-powered solutions in production.
Role Overview:
We are looking for a Software Engineer II with robust backend development expertise and a keen interest in addressing complex data challenges at scale. You will design, build, and optimize distributed systems that extract, enrich, and process metadata for a variety of content. This role involves close collaboration with ML engineers, product managers, and cross-functional teams.
