Engineering Manager, ML​/Data Engineering; Content Trust

Join to apply for the Engineering Manager, ML/Data Engineering (Content Trust) role at Scribd, Inc.

At Scribd Inc. (pronounced “scribbed”), our mission is to spark human curiosity. 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 be bold, debate and commit, embrace plot twists, and prioritize the customer. Our flexible work benefit, Scribd Flex, allows employees to choose the daily work‑style that best suits their needs, with occasional in‑person attendance required for all employees.

We hire for “GRIT”:
Goals, Results, Innovative ideas, and Positive team influence.

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 specialized team responsible for building scalable ML foundations that detect and deal with harmful content, ensuring safety classifiers and automated policy enforcement tools 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 our users.

• 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, operational rigor, and deep empathy for the user safety mission.
• Architect scalable ML data pipelines: design and oversee distributed data processing systems capable of handling hundreds of millions of documents, supporting both batch and real‑time inference.
• Build the “Trust” scores: develop and maintain foundational data layers, including semantic embeddings, metadata extracts, and behavioral signals powering Content Trust ML models.
• Partner on AI/LLM integration: work closely with Search & Discovery and Applied Research teams to integrate ML/LLM‑based reasoning into trust pipelines.
• Drive operational excellence: establish SLAs for infrastructure, ensuring automated enforcement systems are fast and explainable.
• Collaborate cross‑functionally: work with Product Managers (Content Trust), Legal/Policy teams, and Data Science to translate regulatory requirements into robust architectures.

• Leadership experience: 8+ years total engineering experience with 3+ years in a people‑management or technical‑lead role in Data or ML Engineering.
• Scale expertise: proven track record of building and operating production‑grade data pipelines at massive scale (100M+ entities) using Spark, Flink, Kafka, or Airflow.
• ML infrastructure fluency: deep understanding of the ML lifecycle, feature engineering, model deployment (MLOps), and vector databases (Pinecone, Milvus, or Weaviate).
• Trust & safety context: prior experience building systems for content moderation, fraud detection, spam prevention, or digital rights management.
• Technical breadth: strong proficiency in Python, Scala, or Go, and cloud‑native infrastructure (AWS/GCP, Kubernetes, Snowflake/Big Query).
• Strategic communication: ability to explain complex architectural trade‑offs to non‑technical stakeholders in Legal, Policy, and Product.

• LLM pipelines: experience building RAG pipelines or managing infra for fine‑tuning LLMs.
• UGC experience: background working with large‑scale User Generated Content ecosystems.
• Regulatory knowledge: familiarity with technical requirements of global safety regulations such as the Digital Services Act.
• Adversarial mindset: experience building systems that defend against malicious actors and evolving abuse patterns.

Base pay is one part of your total compensation package. In California (San Francisco), salary ranges from $163,000 to $254,500 per year. Outside California, ranges from $134,500 to $241,500 per year. In Canada, ranges from $171,000 CAD to $244,000 CAD. The role also…