History AI Content Quality Assurance Lead

As a History Quality Assurance Lead, you will review AI-generated historical content and work submitted by trainers and quality reviewers. You will check explanations, timelines, comparisons, summaries, source-based answers, and reasoning for accuracy, context, balance, and clarity.

You will use detailed rubrics to find anachronisms, incorrect chronology, unsupported claims, fabricated citations, biased framing, oversimplification, and misleading explanations of cause and effect. You will also identify recurring or serious quality issues, give clear written feedback, escalate concerns when needed, and answer questions about sources and interpretation.

The role also includes maintaining project materials such as style guides, FAQs, trackers, quality notes, examples, calibration tasks, and onboarding documents. You will help communicate guideline changes, support trainer and reviewer onboarding, and identify ways to improve recurring quality gaps and review workflows.

• Review historical content for accuracy, evidence, chronology, context, balance, and clarity.
• Check trainer and quality assurance submissions against project rubrics.
• Explain quality issues precisely through written feedback.
• Support consistent review standards, onboarding, documentation, and workflow improvements.

What It Pays and Takes

This is a remote contractor opportunity for candidates in the United States. The role is listed as entry level, but it requires substantial historical knowledge and at least three years of relevant experience.

• Pay: Up to $50 per hour.
• Time: 20 or more hours per week.
• Location: Remote; open to candidates in the United States.
• Education: A bachelor's, master's, or PhD degree in History, Classics, Area Studies, Archaeology, Political History, Cultural History, International Relations, Humanities, or a closely related field.
• Experience: At least three years in historical research, teaching, writing, editing, academic review, museum or archival work, curriculum development, or a related humanities workflow.
• Knowledge: Historical methods, chronology, primary and secondary sources, historiography, causation, regional context, and evidence-based interpretation.
• Skills: Clear written English, close attention to detail, organized communication, and the ability to apply rubrics and explain findings precisely.
• Helpful experience: A specialization in ancient, medieval, modern, world, military, intellectual, social, economic, colonial or postcolonial, or regional history.
• Helpful background: Remote research, writing, review, education, annotation, or quality assurance teams; AI training, data annotation, language model evaluation, academic quality assurance, fact-checking, or rubric-based review.
• Tools: Comfort with Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems is helpful.

How It Works

Apply on OpenTrain with your resume and then complete the application on the hiring site.

About AI Training Work

AI training is the human work behind systems that generate and evaluate content. Reviewers use subject knowledge to check model responses, find errors, and provide examples and feedback that help AI produce more accurate and useful results.