History Quality Assurance Lead (QAL)

SuperAnnotate AI, Inc.; United States; Remote; USD 57.000 - 81.000; Teilzeit

Zusammenfassung

SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, seeks a History Quality Assurance Lead for remote, hourly contractor work. You will oversee quality across history-focused AI training projects, review AI-generated content, and provide precise feedback to trainers and QAs to uphold client rubrics.

You must have deep history expertise, exceptional written English, and the ability to manage quality workflows across remote teams, contributing to accurate,

Qualifikationen

• Bachelor’s, Master’s, or PhD degree in History or closely related field.
• Strong English skills for guidance and feedback.
• 3+ years in historical research, teaching, writing, editing, or related humanities workflows.
• Understanding of historical methods, chronology, and evidence-based interpretation.
• Ability to evaluate content against rubrics and identify issues like anachronism or biased framing.
• Familiarity with historical specializations is a plus.
• Experience leading or supporting remote research teams is preferred.
• Comfort using Discord, Google Sheets/Docs, and project-tracking tools.

Aufgaben

• Quality monitoring: spot-check history items and provide ongoing feedback.
• Historical review: evaluate AI-generated history explanations for accuracy and context.
• Trainer/QA communication: update teams on new guidelines and rubrics.
• Question handling: respond to questions about chronology and historical context.
• Activation management: DM inactive contributors and flag availability issues.
• Documentation: maintain history project documents, guides, and FAQs.
• Onboarding/training: run calls to explain expectations and workflows.
• Quality alignment: ensure consistent application of guidelines across projects.
• Risk and bias review: flag biased or poorly sourced claims.
• Process improvement: identify recurring gaps and propose scalable QA processes.

Kenntnisse

AI Training

Historiography

Documentation

Source Evaluation

Chronology

Trainer Feedback

Quality Assurance

Remote Team Management

Ausbildung

Bachelor’s / Master’s / PhD in History or related field

Tools

Discord

Google Sheets

Google Docs

Trackers

Dashboards

Project management systems

Jobbeschreibung

Pay: up to $50/hour

In this hourly, remote contractor role, you will work as a History Quality Assurance Lead (QAL) to oversee quality, consistency, and trainer performance across history-focused AI training projects. You will review AI-generated history content and trainer/QA work, evaluate output quality against project guidelines, provide precise written feedback, and ensure that all contributors follow the expected quality standards.

You will assess work for historical accuracy, chronology, source awareness, causation, context, regional and cultural nuance, interpretation quality, clarity, formatting, instruction-following, and adherence to project-specific rubrics. You will spot recurring quality issues, communicate updates to trainers and QAs, support onboarding, maintain documentation, and help activate contributors who are not working consistently. This role requires strong history expertise, strong English communication skills, excellent attention to detail, structured communication, and the ability to manage quality workflows across remote expert teams.

This role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, delivering training data for many of the world’s largest AI companies and foundation-model labs. Your history quality leadership will directly help improve the world’s premier AI models by ensuring that history training data is accurate, contextualized, balanced, well-explained, well-documented, and aligned with client expectations.

Selection process involves an AI interview, a domain-specific task, and an interview with a recruiter.

Important:

There is no immediate project for this role; however, if qualified, you will be among the first experts we reach out to when relevant opportunities arise. This will also provide you with access to future projects available through our expert network.

Responsibilities

• Quality monitoring: Spot-check history items, identify quality issues, provide ongoing feedback through DMs, and escalation 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.

Requirements

• 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.
• 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 is preferred.
• Experience leading or supporting remote teams of researchers, writers, reviewers, educators, annotators, or QAs is strongly preferred.
• Comfortable working in fast-moving remote environments using tools such as Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems.
• Highly detail-oriented and organized, with the ability to maintain style guides, FAQs, trackers, onboarding materials, calibration tasks, and documentation.
• Experience with AI training, data annotation, LLM evaluation, academic QA, fact-checking, or rubric-based review is a strong plus.

Skills: AI Training, Humanities Review, Documentation, Trainer Feedback, Source Evaluation, Chronology, Historiography, history, Historical analysis, LLM evaluation

Open to candidates in: The United States

Interview language: English