
Domain Expert - Art
Listing checked August 26, 2026 · pay as published by Turing
Overview
The role centers on evaluating and improving Large Language Models (LLMs) using deep knowledge of art history, visual arts, architecture, and design. You will design prompts that range from simple to advanced and assess model answers for factual accuracy, reasoning, completeness, and nuance. Each day involves comparing multiple AI outputs, ranking them, and explaining correct or incorrect responses with reliable references. You will also create benchmark datasets and adversarial test cases to expose hallucinations and logical gaps. The position is an 8-week contractor role requiring 40 hours per week with at least 4 hours of PST overlap.
What You'll Do11
- 1Create advanced prompts that cover fine arts, visual arts, architecture, design, art history, museums, and artists.
- 2Evaluate AI-generated responses for factual accuracy, reasoning quality, completeness, and nuance.
- 3Spot hallucinations, logical inconsistencies, outdated information, and edge cases in model outputs.
- 4Develop benchmark datasets and adversarial test cases to challenge model knowledge.
- 5Provide evidence-based feedback with reliable references.
- 6Work with AI researchers to improve model performance.
- 7Keep annotation quality consistent and document decisions.
- 8Write domain-specific prompts at varying difficulty levels.
- 9Compare multiple AI responses and rank them according to quality.
- 10Explain why a response is correct or incorrect using authoritative sources.
- 11Identify ambiguous questions and propose clearer prompt versions.
Requirements8
- 1Master’s degree or higher in any field; degrees in art history, fine arts, visual arts, museum studies, cultural studies, design, humanities, or related disciplines are preferred.
- 2Strong knowledge of major artists, artworks, art movements, styles, periods, techniques, museums, cultural traditions, and developments in visual arts.
- 3At least 3 years of professional experience in art research, academia, museums, galleries, curation, art criticism or journalism, education, publishing, arts and cultural content, or a related field.
- 4Excellent written English, research, and analytical skills.
- 5Strong attention to detail and the ability to assess artistic, historical, and cultural information with accuracy and within the proper context.
- 6Experience with LLMs, generative AI, prompt engineering, or AI evaluation (preferred).
- 7Published research, industry recognition, or teaching experience is a plus.
- 8Ability to work independently and deliver objective, evidence-backed reviews.
Who Should Apply
Candidates with a graduate degree in art history, fine arts, or museum studies and at least 3 years of professional art research experience will thrive in this role. The work demands meticulous evaluation of AI responses, so strong written English and the ability to cite authoritative references are essential. This role is less suitable for people who prefer creating art over analyzing it or who cannot commit to an 8-week contract with a 4-hour PST overlap. Many applicants score low on fit because their domain knowledge is broad but shallow, or because their written explanations do not include specific references from museums, journals, or scholarly sources.
Pay and demand for AI Training roles
AggregatedTypical pay
$70/hour
This role
Pay not disclosed
Most AI Training roles pay $40–$95 per hour.
Based on 1,062 similar roles that publish pay · 304 publish only a top rate; those count at the rate they gave
Rates shown per hour. Yearly and monthly pay converted; one-time fees and non-USD pay are not included.
- Live similar roles
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- Listed in last 30 days
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Hiring most right now: micro1 (353) · SME Careers (256) · Mercor (155)
Most requested skills · share of roles
- ai training13%
- llm evaluation11%
- ai evaluation11%
- data annotation9%
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Compensation
Undisclosed by Turing
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Required Skills
Application Tip
During the assessment, craft prompts that require knowledge of specific art movements and cite authoritative references in your explanations, as the team evaluates factual accuracy and evidence-backed reasoning.
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