[Hiring] Music Content Reviewer (AI Evaluation) @Gramian Consulting Group

Role Description

We are looking for an experienced Music Domain Expert to contribute to the evaluation and improvement of Large Language Models. The role focuses on:

• Creating challenging music-related prompts
• Reviewing AI-generated responses
• Identifying factual and reasoning errors
• Developing high-quality benchmark data

The work may cover:

• Music theory
• Genres
• Composers
• Artists
• Instruments
• Production techniques
• Performance
• Music history

This position is suited to professionals with advanced academic knowledge and practical, research, or teaching experience in music.

• CONTRACT: Contractor assignment, 8 weeks
• COMMITMENT: Full-time, 40 hours per week with at least 4 hours of PST overlap
• LOCATIONS: Remote - Bangladesh, Brazil, Colombia, Egypt, Ghana, India, Indonesia, Pakistan, Turkey, Vietnam
• PROCESS: Initial screening followed by domain manager review

Qualifications

• Master’s degree or higher in Music, Music Theory, Musicology, Composition, Music Production, Performance, or a closely related discipline
• At least 3 years of professional, research, or teaching experience in a music-related field
• Strong knowledge of music theory and at least one additional area such as music history, performance, composition, genres, instruments, or production
• Ability to evaluate complex music-related content for factual, logical, and contextual accuracy
• Experience conducting research and supporting conclusions with reliable references
• Excellent written English communication skills

Requirements

• Create advanced music-related prompts across a range of disciplines and difficulty levels
• Evaluate AI-generated responses for factual accuracy, reasoning quality, completeness, and nuance
• Identify hallucinations, outdated information, logical inconsistencies, and difficult edge cases
• Verify claims related to music theory, artists, composers, genres, instruments, and production
• Develop benchmark datasets and adversarial test cases for model evaluation
• Provide clear, objective, and evidence-based feedback supported by reliable references
• Document findings and maintain high annotation and evaluation standards
• Collaborate with AI researchers and project teams to improve model performance
• Participate in calibration and quality-review activities