Remote Audiobook QA Specialist for AI Narration

Obsidian; San Francisco (CA); Remote; USD 25,000 - 30,000; Part time

Job summary

Obsidian is assembling a team of native English speakers to evaluate AI-narrated audiobooks in US / North American English. You’ll listen like a devoted audiobook fan but with a careful, analytical ear to flag moments where narration slips.

This remote, part-time role offers roughly 20 hours per week. You can work from anywhere, though strong command of English and regular, precise logging of issues will be essential for helping improve our models.

Qualifications

• Native English (US/NA) required or near-native
• Strong attention to detail and careful review
• Experience with annotation, labeling, transcription, proofreading or similar detail-oriented work
• Ability to report clearly and communicate with the team
• Reliable availability for ~20 hours per week on a part-time basis

Responsibilities

• Listen to AI-narrated audiobooks in English and assess how natural, accurate, and enjoyable the narration is.
• Spot and log errors in the synthesized speech — skipped, added, or mispronounced words; numbers read incorrectly; abbreviations expanded wrongly; unnatural phrasing or intonation; audio glitches and artifacts.
• Categorize each issue and mark the exact span where it occurs, using our review tooling.
• Report on overall listener satisfaction and where the narration feels natural versus where it breaks the experience.
• Work consistently and carefully across many hours of audio without losing attention to detail.

Skills

Native English (US/NA)

Attention to detail

Annotation / labeling experience

Transcription / proofreading

Remote collaboration

Job description

Obsidian is assembling a team of native English speakers to evaluate AI-narrated audiobooks in US / North American English. You’ll listen like a devoted audiobook fan but with a careful, analytical ear to flag moments where narration slips.

This remote, part-time role offers roughly 20 hours per week. You can work from anywhere, though strong command of English and regular, precise logging of issues will be essential for helping improve our models.