Engineering Manager, ML / Data Engineering - Content Trust

Overview

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At Scribd Inc. (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. This posting reflects an approved, open position within the organization.

We support a culture where employees can be real and bold; debate and commit; and take action while prioritizing the customer. Scribd Flex allows choosing a daily work-style in partnership with managers, with occasional in-person attendance required for all employees, regardless of location.

We hire for GRIT : goals, results, initiative, and teamwork.

The Team and Role

The ML Data Engineering team builds high-throughput, ML-driven data 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 team responsible for building scalable ML-based foundations that detect and address harmful content. You’ll help enable ML models to reason across our corpus in batch and real-time, ensuring our safety classifiers and automated policy enforcement are performant, scalable, and resilient. You will sit at the intersection of Big Data, AI, MLOps, and Platform Integrity, directly impacting the safety of millions of users.

Responsibilities

• Lead and grow a high-performing engineering team : manage, mentor, and recruit data and ML engineers; foster technical excellence, operational rigor, and user-safety empathy.
• Architect scalable ML data pipelines : design distributed data processing systems for hundreds of millions of documents; support batch and real-time inference for content moderation and risk detection.
• Build foundational data layers : develop semantic embeddings, metadata extracts, and behavioral signals to power Content Trust ML models.
• Partner on AI / LLM integration : collaborate with Search & Discovery and Applied Research to integrate ML / LLM-based reasoning into trust pipelines.
• Drive Operational Excellence : establish SLAs for infrastructure; ensure automated enforcement systems are fast and explainable.
• Cross-functional Leadership : work with Product Managers (Content Trust), Legal / Policy, and Data Science to translate evolving regulatory requirements (e.g., DSA) into robust architectures.

Qualifications

Compensation and Benefits

At Scribd, base pay is part of total compensation and is determined within a range based on location. California salaries range from $163,000 to $254,500; other US locations range from $134,500 to $241,500. In Canada, ranges are CA$171,000 to CA$244,000. We consider factors such as experience, skills, education, and business needs. This position may include equity and a comprehensive benefits package.

Working at Scribd

Are you based in Scribd’s location requirements? Primary residence should be in or near listed cities (US, Canada, or Mexico) with surrounding metro areas within commuting distance.

Benefits, Perks, and Wellbeing

For more about life at Scribd, visit www.linkedin.com / company / scribd / life. If you require reasonable adjustments in the interview process, email accommodations@scribd.com. Scribd is an equal opportunity employer; we value diversity and inclusion.

Related roles and referrals : Senior Manager roles and other Principal Engineering positions are listed for visibility.

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