Sociology Quality Assurance Lead (QAL)

In this hourly, remote contractor role, you will work as a Sociology Quality Assurance Lead (QAL) to oversee quality, consistency, and trainer performance across sociology-focused AI training projects. You will review AI-generated sociology 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 sociological accuracy, theory application, research literacy, social context, methodological rigor, 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 sociology 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 sociology quality leadership will directly help improve the world’s premier AI models by ensuring that sociology training data is accurate, nuanced, ethically aware, research-informed, 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 sociology items, identify quality issues, provide ongoing feedback through DMs, and escalate recurring or critical issues.
• Sociology review: Evaluate AI-generated sociology explanations, theory applications, research summaries, social policy discussions, demographic interpretations, and 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 sociology-specific review standards.
• Question handling: Respond to trainer/QA questions clearly and promptly, especially around sociological concepts, social theory, research methods, inequality, culture, ethics, bias, 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 sociology 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 sociology-specific review requirements.
• Quality alignment: Ensure all trainers and QAs apply sociology review guidelines consistently and understand updates as projects evolve.
• Bias and ethics review: Flag stereotyping, stigmatizing language, unsupported claims about social groups, weak causal reasoning, or ethically problematic social analysis.
• Process improvement: Identify recurring quality gaps, propose workflow improvements, and help build scalable QA processes for sociology AI training projects.

Requirements

• Bachelor’s, Master’s, or PhD degree in Sociology, Social Sciences, Social Research, Demography, Criminology, Gender Studies, Ethnic Studies, Public Policy, Anthropology, 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 sociology research, teaching, social policy analysis, qualitative/quantitative research, academic writing, social science review, community research, or related workflows.
• Strong understanding of sociological theory, social institutions, inequality, stratification, race/ethnicity, gender, class, culture, deviance, organizations, social change, demography, and research methods.
• Ability to evaluate sociology content against detailed rubrics and identify issues such as unsupported generalizations, stereotyping, methodological flaws, weak causal claims, oversimplification, biased framing, or inaccurate use of sociological concepts.
• Familiarity with areas such as survey research, interviews, ethnography, statistical analysis, social policy, urban sociology, family sociology, education, health disparities, work/organizations, or criminology is preferred.
• Experience leading or supporting remote teams of researchers, educators, analysts, reviewers, 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, social science QA, academic review, or rubric-based review is a strong plus.