- 经验
- 任何
- 薪水
- —
- 职位空缺
- 1
- 发布
- 1 个月前
- 工作模式
- 在家办公
- 学历
- Bachelor’s degree in Music, Music Theory, Music Performance, Music Education, or a closely related field
- 合格
- Applicants with a relevant music degree or equivalent professional musician experience may apply. The role is also suitable for people with a background in transcription, lyric annotation, vocal performance, choral work, studio recording, music production, QA, or AI training.
- 恢复
- 需要申请
职位描述
About the role
Handshake AI is hiring detail-focused Music Content Analysts (Fellows) to help build and assess AI systems that work with music. The position is best suited to people with academic training in music or hands-on experience as musicians, especially those with strong listening abilities and a solid grasp of song arrangement and vocal performance.
In this role, you will review audio clips and contribute structured annotations that improve the system’s understanding of lyrics, vocals, and song sections.
Core responsibilities
- Review short song excerpts and compare them against the provided lyrics.
- Spot wording, phrasing, or structural mismatches and revise lyrics for accuracy.
- Analyze vocals to estimate how many singers are present in a track.
- Identify each vocalist’s gender from the audio, based on careful listening and analysis.
- Label song segments such as verse, chorus, bridge, intro, outro, and pre-chorus using the given framework.
- Submit organized, high-quality annotations that follow project instructions.
- Work consistently and maintain accuracy across all evaluations.
Required qualifications
Candidates should have either a bachelor’s degree in Music, Music Theory, Music Performance, Music Education, or a closely related discipline, or professional experience as a performing, recording, or touring musician.
Applicants should also have a sharp ear for pitch, harmony, vocal stacking, and arrangement, along with familiarity with common song structures across genres.
Strong attention to detail and the ability to complete work independently are essential.
Preferred background
- Experience in transcription or lyric annotation.
- Exposure to vocal performance or choral singing.
- Work in studio recording or music production.
- Previous involvement in annotation, quality assurance, or AI training tasks.
Ideal candidate profile
The strongest candidates are attentive listeners with trained musical judgment. They can quickly separate layered vocals, recognize transitions between sections of a song, and catch lyric errors accurately. A methodical working style and comfort with structured review processes are important for success in this role.
Additional information
Location: Remote
Team: Handshake AI
Engagement type: Contract / Fellowship