Cultural Studies QA Lead

Role overview

This contract, hourly remote position is for a Cultural Studies Quality Assurance Lead who will oversee quality control and consistency across art history, visual culture, cultural studies, and humanities-focused AI training projects. The role centers on reviewing AI-generated content and reviewer output, measuring it against project rubrics, and delivering clear written feedback that improves accuracy, nuance, and standards compliance.

You will work with remote expert teams to monitor historical accuracy, visual interpretation quality, cultural context, terminology use, representation sensitivity, clarity, formatting, and instruction adherence. The role also includes identifying repeat issues, helping with onboarding, maintaining documentation, and re-engaging contributors who are not consistently active.

This opportunity sits within a fast-growing AI data services organization that supports major AI companies and foundation-model labs. The work contributes to better humanities training data by making sure outputs are historically grounded, culturally sensitive, visually literate, and aligned with client expectations.

There is no immediate assignment attached to this role. If selected, you will be among the first experts contacted for relevant future projects and may gain access to opportunities through the expert network.

Selection process

The hiring process includes an AI interview, a domain-specific task, and a conversation with a recruiter.

Requirements

• A Bachelor’s, Master’s, or PhD in Art History, Cultural Studies, Visual Culture, Museum Studies, Humanities, Fine Arts, Comparative Literature, Media Studies, Anthropology, History, or a closely related discipline.
• Strong command of English for reading project instructions, coordinating with teams, and producing precise written feedback.
• At least 3 years of experience in art historical research, cultural analysis, museum or curatorial work, teaching, academic writing, visual analysis, editing, cultural criticism, or a related humanities function.
• Solid understanding of art historical methods, iconography, style, periodization, patronage, materials and medium, museum ethics, cultural theory, representation, and historical context.
• Ability to assess art history and cultural studies work against detailed rubrics and detect misattribution, weak visual analysis, inaccurate periodization, cultural stereotyping, unsupported interpretation, outdated terminology, and claims without context.
• Preferred exposure to ancient, medieval, Renaissance, modern, and contemporary art, as well as non-Western art histories, photography, film and media, visual culture, postcolonial theory, gender studies, museum studies, or heritage studies.
• Experience guiding or supporting remote groups of researchers, writers, reviewers, educators, curators, annotators, or QA professionals is strongly preferred.
• Comfort using collaboration and workflow tools such as Discord, Google Sheets, Google Docs, trackers, dashboards, and project management platforms.
• High organization and attention to detail, with the ability to maintain style guides, FAQs, trackers, onboarding assets, calibration exercises, and documentation.
• Prior exposure to AI training, data annotation, LLM evaluation, humanities QA, cultural sensitivity review, image or content review, or rubric-based review is a strong advantage.

Responsibilities

• Carry out quality spot checks on art history and cultural studies items, surface defects, provide feedback through direct messages, and escalate recurring or serious concerns.
• Review AI-generated explanations, visual analyses, cultural comparisons, museum-style writeups, critical interpretations, and context summaries for correctness and nuance.
• Keep trainers and QAs informed in Discord about new guidance, workflow changes, quality expectations, and subject-specific review standards.
• Answer trainer and QA questions quickly and clearly, especially on attribution, periodization, cultural context, interpretive claims, representation, ethics, and rubric interpretation.
• Contact inactive contributors, encourage them to resume work, track follow-ups, and flag availability problems when needed.
• Build and update project documentation such as style guides, trackers, FAQs, quality notes, examples, honeypots, calibration tasks, and onboarding materials.
• Plan and lead onboarding and training calls that explain expectations, workflows, rubrics, quality requirements, and review procedures for the domain.
• Keep trainers and QAs aligned so that review standards are applied consistently as project requirements evolve.
• Identify culturally insensitive, Eurocentric, decontextualized, stereotyping, misattributed, or unsupported claims about art, culture, artists, or communities, and flag them appropriately.
• Recommend process improvements and help develop scalable QA workflows for humanities-focused AI training work.

Additional information

This is a remote contractor role based in Washington, United States. The work is described as hourly and contract-based. A future-project model applies here, meaning there may not be immediate work available, but qualified candidates may be considered first when matching assignments appear.

Selection involves multiple steps, including an AI interview, a domain-specific task, and a recruiter interview. Access to future opportunities through the expert network is part of the overall arrangement if you are qualified.