Sociology QA Lead - Remote

Key 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.

About the role

This hourly, remote contractor role involves overseeing 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.