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# Remote Domain Expert Reviewer - Music

- **Company:** Cornerstone Barricades
- **Location:** San Francisco, CA, United States
- **Experience:** Experienced
- **Salary:** $83,200.0 - $104,000.0
- **Contract:** Contract
- **Skills:** Artificial Intelligence, Large Language Models, Prompt Engineering
- **Published:** August 28, 2026
- **Apply:** https://turing.betterteam.com/remote-domain-expert-reviewer-music-3/apply

## About the Role

* Master's degree or higher in any field; degrees in Music, Music Theory, Musicology, Ethnomusicology, Music Education, Music Production, Audio Engineering, Performing Arts, or other music-related disciplines are preferred.
 * Strong knowledge of music, including music theory, composition, genres, composers, artists, instruments, music history, production techniques, notation, and contemporary music trends.
 * 3+ years of relevant professional experience, preferably in music education, performance, composition, music production, journalism, research, content creation, audio engineering, or a related field.
 * Excellent written English, research, and analytical skills.
 * Strong attention to detail and ability to evaluate music-related information accurately, identify factual inconsistencies, and assess reasoning across diverse musical topics., * Experience reviewing AI-generated content, LLM evaluations, prompt engineering, or annotation quality.
 * Familiarity with quality assurance, editorial review, or content evaluation workflows.
 * Strong knowledge of music theory, genres, composers, artists, instruments, music production, and music history.
 * Ability to provide objective, evidence-based feedback while maintaining consistent quality standards.
 * Experience working independently in a fast-paced, quality-focused environment.

## Description

We are seeking a highly qualified Music Domain Reviewer to support the quality assurance of Large Language Model (LLM) evaluation projects. In this role, you will review domain-specific prompts, evaluate completed tasks for accuracy and quality, ensure adherence to project guidelines, and provide actionable feedback to maintain high annotation standards. Your expertise in music will help ensure the reliability, consistency, and quality of AI evaluation data across diverse music-related topics., * Review and validate domain-specific prompts covering music theory, genres, composers, artists, music history, production, instruments, and related topics.

 * Evaluate completed tasks to ensure factual accuracy, reasoning quality, completeness, and compliance with project guidelines.
 * Identify factual inaccuracies, logical inconsistencies, hallucinations, outdated information, and low-quality annotations.
 * Ensure prompts are challenging, relevant, and aligned with project objectives.
 * Provide clear, constructive, and evidence-based feedback to contributors to improve task quality.
 * Maintain consistency across reviews by following established quality standards and review guidelines.
 * Escalate ambiguous or complex cases when necessary and document review findings.
 * Collaborate with project managers and AI teams to continuously improve evaluation quality and review processes.


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