Music Domain Reviewer for LLM Evaluations

About OpenTrain

OpenTrain AI helps people find and build careers in AI training and data labeling. As the hiring and contracting organization for this role, OpenTrain connects qualified contributors with specialized projects that help improve how modern AI systems work.

• Create a free OpenTrain account and apply in minutes.
• Build experience in a fast-growing field at the intersection of expertise and artificial intelligence.

About AI Training and LLM Evaluation

AI training is the human side of building artificial intelligence. For large language model evaluation projects, specialists review prompts and generated responses, identify errors, and provide feedback that helps make AI outputs more accurate, consistent, and useful.

• Work remotely with a flexible part-time schedule.
• Help shape the quality and reliability of cutting-edge language models.
• Apply your subject expertise to prompts and responses across diverse music topics.

The Role

OpenTrain AI is hiring a Music Domain Reviewer to support quality assurance for large language model evaluation projects. You will review music-related prompts, assess completed AI-generated tasks, and provide evidence-based feedback that maintains consistent annotation and evaluation standards.

The role is listed at the entry level, while the requirements call for a master's degree or higher and at least three years of relevant professional experience in a music-related field. The expected time commitment is 20 or more hours per week as a part-time contractor.

• Work type: Part-time contract
• Time requirement: 20+ hours per week
• Work arrangement: Remote and worldwide
• Working language: English

What You'll Do

You will evaluate content across music theory, genres, composers, artists, music history, production, instruments, notation, and related subjects. Your reviews will focus on factual accuracy, reasoning quality, completeness, relevance, and compliance with project guidelines.

• Review and validate domain-specific music prompts.
• Evaluate completed tasks for accuracy, reasoning quality, completeness, and guideline compliance.
• Identify factual inaccuracies, logical inconsistencies, hallucinations, outdated information, and low-quality annotations.
• Check that prompts are challenging, relevant, and aligned with project objectives.
• Provide clear, constructive, evidence-based feedback to contributors.
• Follow established quality standards to keep reviews consistent.
• Escalate ambiguous or complex cases when necessary and document review findings.
• Collaborate with project managers and AI teams to improve evaluation quality and review processes.

Requirements

You should have advanced knowledge of music and the ability to assess music-related information accurately across a broad range of topics. Strong written English, research ability, analytical judgment, and attention to detail are essential for evaluating both facts and reasoning in generated outputs.

• Master's degree or higher in any field.
• Preferred academic background in Music, Music Theory, Musicology, Ethnomusicology, Music Education, Music Production, Audio Engineering, Performing Arts, or another music-related discipline.
• Strong knowledge of music theory, composition, genres, composers, artists, instruments, music history, production techniques, notation, and contemporary music trends.
• At least three 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.
• Ability to identify factual inconsistencies and evaluate reasoning across diverse musical topics.
• Expertise in music theory, genre, and history within a relevant domain.

Helpful Background

Experience with AI-generated content or quality-focused review workflows can help you contribute effectively, although the core requirement is strong music expertise and careful evaluation.

• Experience reviewing AI-generated content or LLM evaluations.
• Familiarity with prompt engineering or annotation quality.
• Background in quality assurance, editorial review, or content evaluation.
• Ability to work independently in a fast-paced, quality-focused environment.

How to Apply Through OpenTrain

Create a free OpenTrain account, build your contributor profile, and apply for this Music Domain Reviewer contract in minutes. Your expertise can help improve AI evaluation data while you develop experience in one of the fastest-growing areas of tech work.

• Apply remotely from anywhere in the world.
• Commit 20 or more hours each week.
• Use your professional music knowledge to influence AI quality.