History Quality Assurance Lead (QAL)
SME Careers • Remote
Education
PhD
Type
Hourly
Pay Rate
$50/hr
Listed
53d ago
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- Interview
- Required i As stated in the listing: “Selection process involves an AI interview, a domain-specific task, and an interview with a recruiter.”
About this role
From the SME Careers listing
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.
How long hiring takes
Across the AI training platforms we refer candidates to, the median gap between referral and hire is about 30 days. It varies by platform and role, so treat it as a rough guide for this one.
Why this role
This History Quality Assurance Lead role pays $50 per hour to oversee AI-generated history content across chronology, causation, and regional context. Reviewers check source awareness and interpretation quality specifically, so the job involves catching where an AI response cites a source uncritically or flattens a historical debate into a single accepted answer. It fits a historian comfortable with historiography, someone who reads a source critically rather than recalling dates and names.
Skills and categories
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Common questions
Does SME Careers offer a path for advancement?
Yes. SME Careers is unusual among AI training platforms for this: it publishes an explicit career ladder, Data Trainer, then Quality Analyst, then QA Lead, then Project Manager. Consistent, high-quality work is what moves you up it.
How does SME Careers pay freelancers?
Weekly, through Deel. Deel also handles tax compliance, which is how SME Careers pays contractors across more than 40 countries without running its own international payroll.
What does asynchronous AI training work mean in practice?
No set hours, no check-ins, no meetings. You log in when you want, pick up an available task, complete it, and submit; nobody is waiting on you in real time. That's different from remote employment, where you're expected online during business hours. The tradeoff: you're competing with others for available tasks, so an empty queue means there's simply nothing to do until more work is released.
What does QA Testing work look like for a History Quality Assurance Lead (QAL)?
Tasks here are scoped to QA Testing, not generic labeling. As a History Quality Assurance Lead (QAL), expect to draw on real domain judgment (evaluating outputs, correcting errors, or providing expert reasoning specific to QA Testing) rather than following a one-size-fits-all rubric. If you don't have hands-on QA Testing background, this is likely not the right listing to start with.
What specific skills does this listing call for?
AI Training, Humanities Review, Documentation, and Trainer Feedback are named directly in the listing. If you don't have hands-on experience with these, expect the screening process to test for them directly rather than accepting adjacent experience as a substitute.
How much does this specific role pay?
This listing is posted at $50/hr, a per-task rate. Pay can change between when we last checked the listing and when you apply, so confirm the current number on the platform's own application page before committing time.
What happens when I click Apply on this listing?
You'll be taken to SME Careers's external site to complete your application there. This listing links through a referral, but the process is identical to applying directly; the link just routes you correctly. Create an account on their site and follow their onboarding steps.
Is a PhD required?
For this specific role, yes, or near-equivalent professional depth. The credential gate is enforced at the assessment stage, not just on paper. That said, active PhD candidates and people with equivalent published research have qualified without a formal degree. The assessment is the real filter.
Is there an interview?
Yes. Selection process involves an AI interview, a domain-specific task, and an interview with a recruiter.
Who is behind SME Careers?
SME Careers is the expert talent division of SuperAnnotate, an AI data infrastructure platform, connecting domain experts with high-level AI training projects.