Engineering Manager, ML​/Data Engineering; Content Trust

Engineering Manager, ML/Data Engineering (Content Trust)

Scribd Inc. sparks human curiosity by creating a world of stories and knowledge. Our four products—Everand, Scribd, Slideshare, and Fable—empower collective expertise and democratize the exchange of ideas and information.

The ML Data Engineering team builds high‑throughput, ML‑driven pipelines that process hundreds of millions of documents to detect, classify, and mitigate untrustworthy content. As the Manager of ML Data Engineering, you will lead a specialized team that designs scalable ML foundations for detecting and dealing with harmful content, ensuring that safety classifiers and automated policy enforcement tools are performant, scalable, and resilient.

• Lead and grow a high‑performing engineering team:
  Manage, mentor, and recruit a world‑class team of data and ML engineers, fostering a culture of technical excellence and deep empathy for the user safety mission.
• Architect scalable ML data pipelines:
  Design and oversee the development of distributed data processing systems capable of handling hundreds of millions of documents, supporting both batch and real‑time inference for content moderation and risk detection.
• Build the "Trust" scores:
  Develop and maintain the foundational data layers—including semantic embeddings, metadata extracts, and behavioral signals—that power our Content Trust ML models.
• Partner on AI/LLM Integration:
  Work closely with Search & Discovery and Applied Research to integrate ML/LLM‑based reasoning into trust pipelines, enabling nuanced understanding of complex policy violations.
• Drive Operational Excellence:
  Establish SLAs for infrastructure, ensuring our automated enforcement systems are both fast and explainable.