Thriveth

The AI job market, made clearer

Find work worth
your expertise.

Back to all jobs

Social Sciences & Education Team Lead

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.

IndiaUp to $20 per hour
Hiring companySME Careers by SuperAnnotate
Application processN/ANo approved reviews yet
Work experienceN/ANo approved reviews yet

About the role

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.

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.

Why Work with SME Careers?

  • Be a part of a forward-thinking team and help us train AI to communicate more effectively.
  • Shape the Future of AI

    Your work directly contributes to how AI systems learn and communicate.

  • Your Schedule, Your Rules

    Set your own hours and work around your life.

  • Weekly Pay

    Receive fast, reliable payments once work is approved.

  • Community Rewards

    Get rewarded for referrals with ongoing bonus income.

Responsibilities

  • Quality monitoring: Spot-check social science and education items, identify quality issues, provide ongoing feedback through DMs, and escalate 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.

Experience and education

  • Bachelor’s, Master’s, PhD, teaching credential, or equivalent professional experience in Education, Sociology, Psychology, Anthropology, Political Science, Social Work, Public Policy, Educational Psychology, Curriculum Studies, or a related field.
  • 3+ years of experience in teaching, curriculum development, social science research, educational content review, instructional design, academic writing, social policy, student assessment, or related review workflows.
  • Strong understanding of social science concepts, education theory, pedagogy, learning outcomes, assessment design, research methods, ethics, bias, culture, social institutions, inequality, and evidence-based reasoning.
  • Ability to evaluate social science/education content against detailed rubrics and identify issues such as unsupported generalizations, stereotyping, weak causal claims, poor instructional design, biased framing, flawed methodology, or age-inappropriate educational content.
  • Familiarity with areas such as classroom learning, assessment, lesson planning, social research, qualitative/quantitative methods, educational equity, child development, learning science, or curriculum standards is preferred.
  • Experience leading or supporting remote teams of educators, researchers, curriculum writers, reviewers, annotators, trainers, 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, honeypots, calibration tasks, and documentation.
  • Experience with AI training, data annotation, LLM evaluation, social science QA, educational QA, curriculum review, or rubric-based review is a strong plus.

Language requirements

  • Strong grasp of the English language to follow project guidelines, communicate with teams, and provide clear written feedback.
  • Interview language: English.

Assessment requirements

Required

Eligibility

Work arrangement: Fully remote

Eligible countries: India

Compensation details

Up to $20 per hour.

More about the hiring companySME Careers by SuperAnnotate
Find AI-training work. Know what to expect.

Thriveth makes AI data-training work easier to find, understand, and navigate. We replace uncertainty with clear opportunities, realistic expectations, and insights from real application journeys.