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Job Summary:
YO IT Consulting is a fast-growing AI Data Services company delivering training data for many of the world’s largest AI companies and foundation-model labs. They are seeking a History Quality Assurance Lead to oversee quality and consistency across history-focused AI training projects, reviewing AI-generated content and providing feedback to ensure adherence to quality standards. This role requires strong history expertise and excellent communication skills to manage workflows across remote teams.
Responsibilities:
• Quality monitoring: Spot-check history items, identify quality issues, provide ongoing feedback through DMs, and escalate recurring or critical issues.
• Historical review: Evaluate AI-generated history explanations, timelines, comparisons, summaries, source-based answers, and reasoning for accuracy, context, balance, and clarity.
• Trainer and QA communication: Update trainers and QAs on Discord about new item guidelines, project changes, workflow updates, quality expectations, and history-specific review standards.
• Question handling: Respond to trainer/QA questions clearly and promptly, especially around chronology, historical context, source interpretation, disputed interpretations, bias, regional nuance, and rubric interpretation.
• Trainer/QA activation management: DM contributors who are inactive or not working, encourage activation, track follow-ups, and flag availability issues when needed.
• Documentation: Create and maintain history project documentation, including style guides, trackers, FAQs, quality notes, examples, honeypots, calibration tasks, and onboarding materials.
• Onboarding and training: Schedule and run onboarding/training calls with trainers and QAs to explain project expectations, workflows, rubrics, quality standards, and history-specific review requirements.
• Quality alignment: Ensure all trainers and QAs apply historical-review guidelines consistently and understand updates as projects evolve.
• Risk and bias review: Flag misleading, overconfident, biased, culturally insensitive, anachronistic, or poorly sourced historical claims.
• Process improvement: Identify recurring quality gaps, propose workflow improvements, and help build scalable QA processes for history AI training projects.
Qualifications:
Required:
• 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.
• Strong grasp of the English language to follow project guidelines, communicate with teams, and provide clear written feedback.
• 3+ years of experience in historical research, teaching, writing, editing, academic review, museum/archival work, curriculum development, or related humanities workflows.
• Strong understanding of historical methods, chronology, primary vs secondary sources, historiography, causation, continuity/change, regional context, and evidence-based interpretation.
• Ability to evaluate historical content against detailed rubrics and identify issues such as anachronism, incorrect chronology, unsupported claims, oversimplification, biased framing, fabricated citations, or misleading causal explanations.
• Highly detail-oriented and organized, with the ability to maintain style guides, FAQs, trackers, onboarding materials, calibration tasks, and documentation.
Preferred:
• Familiarity with one or more historical specializations such as ancient history, medieval history, modern history, world history, military history, intellectual history, social history, economic history, colonial/postcolonial history, or regional history.
• Experience leading or supporting remote teams of researchers, writers, reviewers, educators, annotators, or QAs.
• Comfortable working in fast-moving remote environments using tools such as Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems.
• Experience with AI training, data annotation, LLM evaluation, academic QA, fact-checking, or rubric-based review.
Company:
Our Core mission is to develop, deploy, or integrate artificial intelligence (AI) — including machine learning (ML), data analytics, automation, natural language processing (NLP), computer vision, and related technologies — to solve real-world problems, improve decision-making, automate repetitive tasks, and deliver intelligent solutions across industries. Founded in 2018, the company is headquartered in Abu Dhabi, Abu Dhabi Emirate, AE, , with a team of 51-200 employees. The company is currently Growth Stage.