Music Professional - AI Music Evaluation
Listing checked September 18, 2026 · pay as published by Handshake AI
Overview
Handshake AI seeks experienced music professionals for a part-time, remote fellowship. The work centers on evaluating AI-generated music and building reference material that helps models grasp styles, traditions, and cultural context. Contributors draw on hands-on skill in instrumental performance, composition, or music production to judge accuracy and relevance. Projects run on an asynchronous schedule, with most participants logging 5 to 20 hours per week during active assignments. No background in AI is needed, and a master's degree or higher is required, with a DMA preferred.
What You'll Do8
- 1Review AI-generated tracks, excerpts, and musical passages for accuracy, style, and cultural fit.
- 2Write detailed evaluations that explain where a model's output succeeds, misses context, or confuses musical traditions.
- 3Create expert training examples from your own performance, composition, or production work.
- 4Compare AI responses against accepted practices in jazz, commercial music, or instrumental performance.
- 5Use Pro Tools, Logic Pro, or Ableton to inspect audio and document specific musical elements.
- 6Flag errors in rhythm, harmony, instrumentation, and genre conventions.
- 7Provide written feedback that helps researchers improve model behavior across diverse musical styles.
- 8Meet project deadlines and follow task guidelines for each assignment.
Requirements8
- 1Master's degree or above in music or a related field.
- 2DMA preferred.
- 3Background in composition, jazz performance, guitar performance, commercial music, or instrumental performance such as saxophone or trumpet.
- 4Strong instrumental performance history, with performance-focused degrees preferred over musicology or ethnomusicology.
- 5Familiarity with Pro Tools, Logic Pro, or Ableton is a plus, not a requirement.
- 6Clear writing and close attention to detail.
- 7Ability to work on your own in a remote, asynchronous setup.
- 8No prior AI experience required.
Who Should Apply
Candidates with a master's degree in performance and a deep background on a primary instrument fit this fellowship best. A DMA, a jazz or commercial music focus, or serious studio time with Pro Tools, Logic Pro, or Ableton adds weight to an application. The project suits musicians who can explain their craft in writing and manage their own schedule. It fits less well for people whose degrees lean toward musicology or ethnomusicology, or for anyone who needs a fixed schedule. Reviewers often reject applicants who list performance credits without showing analytical writing, or who lack the required master's degree. Candidates also score low when they cannot describe how they judge AI-generated music for accuracy and relevance.
Salary Insight
The listing offers up to $100.00 per hour for this fellowship. That figure places the work at the high end of expert AI evaluation projects, which matches the advanced degree and specialized performance background the role asks for. Because the schedule is project-based and part-time, actual earnings depend on how many active hours you take on during a given project.
Pay and demand for AI Training roles
AggregatedTypical pay
$70/hour
This role
up to $100/hr
Most AI Training roles pay $40–$98 per hour. This role's pay sits above that range.
Based on 1,035 similar roles that publish pay · 302 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.
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Most requested skills · share of roles
- ai training14%
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Compensation
Up to $100/hr
Required Skills
Application Tip
Lead with your master's or DMA, name your primary instrument, and state the performance degree you hold. List the DAWs you use, especially Pro Tools, Logic Pro, or Ableton, even if the listing calls them optional. Add a short written sample that critiques an AI-generated track or a recorded performance, because reviewers need proof of your ear and your analytical writing. Quantify your experience where you can, such as years of performance, number of compositions, or studio projects completed.
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