Job Title: Cultural Studies Quality Assurance Lead
Job Type: Contract
Location: Remote
In this hourly, remote contractor role, you will work as an Cultural Studies Quality Assurance Lead to oversee quality, consistency, and trainer performance across art history, visual culture, cultural studies, and humanities AI training projects. You will review AI-generated art history/cultural studies 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, visual-analysis quality, cultural context, terminology accuracy, interpretive nuance, source awareness, representation 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 art history/cultural studies 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 a fast-growing AI Data Services company delivering training data for many of the world’s largest AI companies and foundation-model labs. Your art history/cultural studies quality leadership will directly help improve the world’s premier AI models by ensuring that humanities training data is accurate, culturally sensitive, visually literate, historically grounded, well-explained, 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.
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