Social Sciences & Education Team Lead

Pay: up to $20/hour

In this hourly, remote contractor role, you will work as a Social Sciences & Education Quality Assurance Lead (QAL) to oversee quality, consistency, and trainer performance across social science, education, and learning-focused AI training projects. You will review AI-generated social science/education 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 conceptual accuracy, research literacy, educational appropriateness, social context, methodology quality, ethical awareness, bias sensitivity, 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 social science and/or education 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 Super Annotate, delivering training data for many of the world’s largest AI companies and foundation-model labs. Your social sciences and education quality leadership will directly help improve the world’s premier AI models by ensuring that social science and education training data is accurate, nuanced, research-informed, ethically aware, and aligned with client expectations.

• Quality monitoring:
  Spot-check social science and education items, identify quality issues, provide ongoing feedback through DMs, and elevate recurring or critical issues.
• Social science and education review:
  Evaluate AI-generated explanations, lesson content, social science summaries, research-methods content, educational activities, assessment items, learning guidance, and social reasoning for accuracy and nuance.
• Trainer and QA communication:
  Update trainers and QAs on Discord about new item guidelines, project changes, workflow updates, quality expectations, and social science/education-specific review standards.
• Question handling:
  Respond to trainer/QA questions clearly and promptly, especially around education concepts, learning objectives, research methods, social context, bias, student appropriateness, 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 social sciences/education 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 social science/education-specific requirements.
• Quality alignment:
  Ensure all trainers and QAs apply social science and education review guidelines consistently and understand updates as projects evolve.
• Bias and ethics review:
  Flag stereotyping, stigmatizing language, unsupported claims about groups, weak causal reasoning, poor educational scaffolding, or ethically problematic content.
• Process improvement:
  Identify recurring quality gaps, propose workflow improvements, and help build scalable QA processes for social science and education AI training projects.

• Bachelor’s, Master’s, PhD, teaching credential, or equivalent professional experience in Education, Sociology, Psychology,…