Film & Television Reviewer (AI Evaluation)

Gramian Consulting Group
Remote

About The Position

Gramian Consultancy is seeking an experienced Film & Television Domain Expert to evaluate and enhance Large Language Models. This role focuses on creating complex prompts, comparing AI-generated content, and assessing its accuracy, reasoning, completeness, and nuance within the film and television domain. The expert will cover topics such as film, television, streaming, actors, directors, genres, awards, franchises, and entertainment history.

Requirements

  • Master’s degree or higher in Film Studies, Television Studies, Media Studies, Cinema Studies, Screen Studies, or a closely related discipline.
  • At least 3 years of professional, research, or teaching experience related to film, television, media, or entertainment.
  • Strong knowledge across film, television, streaming, actors, directors, genres, awards, franchises, or entertainment history.
  • Ability to research and verify entertainment-related claims using authoritative sources.
  • Strong analytical skills and ability to assess factual and contextual accuracy.
  • Excellent written English.
  • Strong attention to detail.
  • Ability to work independently and provide objective, evidence-backed reviews.

Responsibilities

  • Create advanced film and television prompts across a range of topics and difficulty levels.
  • Evaluate and rank multiple AI-generated responses.
  • Verify claims related to films, TV shows, streaming content, actors, directors, awards, genres, and franchises.
  • Identify factual inaccuracies, hallucinations, outdated information, logical inconsistencies, and edge cases.
  • Explain why responses are correct or incorrect using reliable references.
  • Identify ambiguous or weak questions and propose improved prompts.
  • Develop benchmark datasets and adversarial test cases.
  • Provide clear, objective, and evidence-based feedback.
  • Maintain accurate documentation and consistent annotation quality.
  • Collaborate with AI researchers and project teams to improve model performance.
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