History Quality Assurance Lead (QAL)
SME Careers • Remote
Education
Any
Type
Pay Rate
$50/task
Listed
1d ago
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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.
### Key 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.
### Your Profile
- 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.
🌍 Geographic Availability
This role is available to qualified experts globally. However, as a U.S.-based company, SME Careers complies with U.S. export control and sanctions regulations. Eligibility depends on your country of residence and any applicable trade restrictions. Some projects may have additional language or region-specific requirements.
💰 Pay Rate May Vary Based on Your Location
Your actual compensation will be determined based on your location and local market conditions. See regional job listings for localized pay information, or the application process will clarify your specific rate.
If you're unsure whether you're eligible, proceed with the application—SME's screening will determine your jurisdiction status and applicable compensation.
Requirements
- Advanced degree or strong hands-on professional experience in the domain
- Ability to pass domain-specific qualification assessments
- Eligible to create a verified account on Deel (for payments/compliance)
- Proficiency in English (for instructions and feedback)
- Available to applicants in 40+ countries
Compensation Analysis
Don't just label data—build a career. SME Careers is unique in the AI training space because it offers a transparent growth ladder. High performers aren't just kept in the queue; they are promoted to Quality Analysts and Project Managers. With weekly transparent payments via Deel and the freedom to work on your own schedule, this is built for modern experts who want long-term engagement.
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Frequently Asked Questions
Is there room for advancement?
Yes. This is a key feature of the platform. They explicitly list a career path: Data Trainer -> Quality Analyst -> QA Lead -> Project Manager. Consistent high-quality work can lead to leadership roles.
How do payments work?
Payments are processed weekly through Deel. This ensures tax compliance and allows them to hire freelancers from over 40 countries securely.
Is the work ongoing or project-based?
Work is project-based, which means assignments can vary in duration and availability. However, top performers often get priority access to new projects.
What does the work actually look like?
It is practical, hands-on data work. You might be recording short videos, categorizing images, rating text responses, or analyzing data. The tasks are designed to be short and distinct—typically 5-60 minutes per task.
How flexible is the schedule?
Extremely. This is true "log in and work" flexibility. You can usually work for 20 minutes or 4 hours depending on your availability. There are rarely minimum hour requirements, making it ideal for side income.
Is there an interview?
Usually, no. Hiring for these roles is almost entirely based on passing an automated assessment or "qualification" task. If you pass the test, you get access to the work.
Who is behind SME Careers?
SME Careers is the expert talent division of SuperAnnotate, a leading AI data infrastructure platform. They connect domain experts with high-level AI training projects.