AI Content Manager Job in San Francisco, CA

Data Labeler

We are looking for a Data Labeler to support high-quality dataset preparation for machine learning initiatives in San Francisco, California. This long-term contract position focuses on reviewing and organizing text, image, audio, and video content so AI models can be trained with reliable, well-structured information. The ideal candidate brings strong editorial judgment, accuracy, and the ability to apply detailed standards consistently across large volumes of content.

Responsibilities:

• Evaluate and label content across multiple data formats, including written material, images, audio files, and video, using defined annotation standards.
• Apply tags, classifications, and descriptive markers to datasets so they can be used effectively in AI and machine learning training workflows.
• Inspect content for quality, completeness, and consistency, correcting issues and flagging unclear or unusual cases for further review.
• Annotate visual assets by identifying relevant elements, outlining objects, or marking important features based on project requirements.
• Review language-based content to classify topics, sentiment, entities, intent, or other attributes needed for model development.
• Transcribe and enrich audio-based materials when required, ensuring accurate interpretation and documentation.
• Maintain productivity and quality benchmarks while handling recurring tasks with a high level of precision and organization.
• Partner with technical and quality teams to refine labeling practices and improve the usefulness of training datasets.