Software Engineer (Backend, Python) - Content Understanding (Toronto)
toronto, on, Canada • Posted June 04, 2026
Job Type:
Full-time
Location:
toronto, on
Posted:
June 04, 2026
Category:
Other-General
Application Deadline:
July 14, 2026
Role Description
The ML Content Understanding Team
The ML Content Understanding team powers metadata extraction, enrichment, and content understanding across all Scribd brands. We process hundreds of millions of documents and billions of images to deliver high‑quality metadata that enables content discovery and trust for millions of users worldwide. Role Overview
We are seeking a Software Engineer II with strong backend development experience to design, build, and optimize distributed systems that extract, enrich, and process metadata for a wide range of content. The role involves working closely with ML engineers, product managers, and cross‑functional partners to integrate machine‑learning models and LLM‑based services into production pipelines and deliver high‑performance solutions at a global scale. Key Responsibilities
Design and build scalable systems to extract, enrich, and process metadata from millions of documents, images, and audio content. Leverage LLMs to integra...
The ML Content Understanding team powers metadata extraction, enrichment, and content understanding across all Scribd brands. We process hundreds of millions of documents and billions of images to deliver high‑quality metadata that enables content discovery and trust for millions of users worldwide. Role Overview
We are seeking a Software Engineer II with strong backend development experience to design, build, and optimize distributed systems that extract, enrich, and process metadata for a wide range of content. The role involves working closely with ML engineers, product managers, and cross‑functional partners to integrate machine‑learning models and LLM‑based services into production pipelines and deliver high‑performance solutions at a global scale. Key Responsibilities
Design and build scalable systems to extract, enrich, and process metadata from millions of documents, images, and audio content. Leverage LLMs to integra...
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