History Quality Assurance Lead

About OpenTrain

OpenTrain AI is hiring a History Quality Assurance Lead for contract-based AI training work. OpenTrain is the #1 platform for finding and building careers in AI training and data labeling, helping contributors discover specialized projects, build a professional profile, and apply in minutes.

In this role, you will bring expert historical judgment to the development and review of AI systems. You will work remotely with expert teams while helping establish consistent quality standards for history-focused training workflows.

• Contractor and part-time engagement
• Based in the United States
• 20+ hours per week
• Pay: $50 USD per hour
• Working language: English

About AI Training and Quality Assurance

AI training is the human side of building artificial intelligence. People prepare, review, and evaluate examples so modern AI models can produce more accurate, useful, and responsible responses.

For history projects, expert reviewers assess explanations, timelines, source-based answers, and reasoning. Your feedback will help identify factual errors, anachronisms, unsupported claims, and misleading interpretations so training data and model outputs meet rigorous standards.

• Contribute directly to the quality of emerging AI systems
• Use historical expertise in a growing technology field
• Work remotely with flexible, project-based AI training teams

The Role

As a History Quality Assurance Lead, you will review AI-generated history content and trainer QA work for accuracy, chronology, source awareness, context, clarity, and rubric adherence. You will provide precise written feedback, monitor quality trends, support onboarding, maintain documentation, and help keep history training workflows consistent across remote expert teams.

This intermediate-level contractor role is suited to someone with a strong background in historical methods, historiography, chronology, and evidence-based interpretation who can make careful judgments against detailed rubrics.

• Evaluate history content and QA work using detailed quality rubrics
• Provide structured feedback to trainers and reviewers
• Help improve consistency across history-focused AI training projects

What You'll Do

You will combine subject-matter expertise with organized quality operations. The work includes reviewing historical reasoning, communicating quality expectations, and maintaining the materials that help distributed teams produce reliable training data.

• Review history explanations, timelines, comparisons, summaries, source-based answers, and reasoning for quality and accuracy.
• Check for anachronism, incorrect chronology, unsupported claims, biased framing, misleading causal explanations, and weak source handling.
• Communicate updates, questions, and quality expectations to trainers and QAs through remote collaboration channels.
• Maintain style guides, FAQs, trackers, examples, calibration tasks, onboarding materials, and other project documentation.
• Spot recurring issues, propose workflow improvements, and help scale quality processes for history training projects.

Required Qualifications

You should be able to evaluate historical content carefully, explain your reasoning clearly, and identify problems in evidence, chronology, context, and causation. Experience in historical research, teaching, writing, editing, academic review, archival work, museum work, or similar humanities workflows is relevant.

• Strong history background across historical methods, historiography, chronology, and evidence-based interpretation.
• Ability to evaluate historical content against detailed rubrics with careful judgment.
• Clear written English communication and organized, structured feedback.
• Experience in historical research, teaching, writing, editing, academic review, archival work, museum work, or similar humanities workflows.
• Familiarity with AI training, data annotation, LLM evaluation, fact-checking, or rubric-based review is a strong advantage.

Helpful Background

The project welcomes a range of historical specialties and professional experiences. Your specific area of expertise can help inform the review of content spanning different periods, regions, methods, and subjects.

• A degree in History, Classics, Area Studies, Archaeology, Political History, Cultural History, International Relations, Humanities, or a closely related field.
• Experience leading or supporting remote teams of researchers, writers, reviewers, educators, annotators, or QAs.
• Comfort working with Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems.
• Specialization in ancient, medieval, modern, world, military, intellectual, social, economic, colonial, postcolonial, or regional history.

Why Build an AI Training Career Through OpenTrain

AI training and data labeling are among the fastest-growing ways to work in technology. Contributors with expertise in fields such as history help shape how AI systems understand evidence, explain complex topics, and respond to users.

OpenTrain helps people start and grow careers in this industry by bringing opportunities together, supporting professional profiles, and making it easier to apply and track experience. Creating an OpenTrain account is free.

• Apply your history expertise to cutting-edge AI development
• Build a portfolio of experience in AI training and quality review
• Find remote, project-based work aligned with your specialist knowledge

How to Apply

If you want contract-based history review work that combines deep subject expertise with quality assurance and AI training oversight, create a free OpenTrain account and apply in minutes. Be prepared to demonstrate your ability to assess historical claims, identify anachronism or weak causation, and provide precise written feedback.

• Review the role requirements and confirm availability for 20+ hours per week.
• Apply through OpenTrain as a US-based contractor.
• Highlight relevant historical research, writing, editing, review, teaching, archival, or AI evaluation experience.