Art History & Cultural Studies Quality Assurance Lead (QAL)

Job Summary

As an Art History & Cultural Studies Quality Assurance Lead (QAL), you will oversee quality, consistency, and contributor performance across art history, visual culture, cultural studies, museum studies, and humanities-focused AI training projects.

You will review AI-generated art history and cultural studies content, visual analyses, cultural interpretations, museum-style descriptions, and trainer/QA submissions to ensure outputs are historically accurate, culturally sensitive, visually informed, and aligned with project standards.

Your work will directly contribute to improving advanced AI systems by ensuring humanities training data reflects strong visual literacy, contextual understanding, interpretive rigor, and ethical awareness.

Key Responsibilities

Quality Monitoring

• Review art history and cultural studies tasks and QA outputs
• Identify recurring quality issues, provide detailed written feedback, and escalate critical quality concerns

Humanities Review

• Review and evaluate art historical explanations, visual analyses, cultural comparisons, museum-style object descriptions, critical interpretations, historical context summaries, visual culture discussions, heritage and museum content, media and representation analyses, and humanities-based reasoning
• Assess work for historical accuracy, visual analysis quality, cultural context, terminology accuracy, interpretive nuance, source awareness, representation sensitivity, clarity, instruction adherence, and rubric compliance

Trainer & QA Communication

• Communicate guidelines, workflow changes, quality standards, humanities review expectations, and evaluation criteria

Contributor Support

• Answer questions involving visual analysis, attribution, periodization, cultural context, interpretation, representation, museum ethics, art historical methods, cultural theory, and rubric interpretation

Activation Management

• Follow up with inactive contributors, track engagement and participation, escalate availability concerns when needed

Documentation & Onboarding

• Create and maintain style guides, documentation, FAQs, quality notes, examples, calibration tasks, and onboarding resources
• Conduct onboarding and training sessions for contributors

Bias & Ethics Review

• Identify and flag cultural stereotyping, Eurocentric framing, misattribution, unsupported interpretations, decontextualized claims, outdated terminology, representation issues, culturally insensitive analysis, and heritage and museum ethics concerns

Process Improvement

• Improve QA workflows and identify recurring quality gaps
• Develop scalable humanities review processes

Required Qualifications

• 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 related disciplines
• Strong English communication skills
• Minimum 3 years of experience in art historical research, cultural analysis, museum or curatorial work, teaching, academic writing, visual analysis, editing, or cultural criticism
• Strong understanding of Art Historical Methods, Visual Analysis, Iconography, Style & Periodization, Patronage, Materials & Media, Museum Ethics, Cultural Theory, Representation, and Historical Context
• Ability to identify misattributions, incorrect periodization, weak visual analysis, cultural stereotyping, unsupported interpretation, outdated terminology, and decontextualized claims

Preferred Qualifications

• Experience with Ancient Art, Medieval Art, Renaissance Art, Modern & Contemporary Art, Non-Western Art Histories, Photography, Film & Media Studies, Postcolonial Theory, Gender Studies, Heritage Studies, and Museum Studies
• Experience with AI Training, Data Annotation, LLM Evaluation, Humanities QA, Cultural Sensitivity Review, Image Review, and Rubric-Based Evaluation

Why Join

• Help improve leading AI systems through humanities quality assurance
• Flexible remote schedule
• Weekly payments
• Access to future opportunities through SME Careers' expert network

Selection Process

1. AI Interview
2. Domain Assessment
3. Recruiter Interview

Important Note

There is currently no active project for this role. Qualified candidates will be added to the SME Careers expert network and contacted when art history, visual culture, museum studies, or cultural studies opportunities become available.