Audiobook QA Expert — Portuguese (Brazil)

Official role description

Help make the next generation of AI-narrated audiobooks sound genuinely human.

1. Overview

We're building a team of native Portuguese speakers who love audiobooks to help evaluate AI-narrated (text-to-speech) audiobooks in Brazilian Portuguese. You'll listen the way a real audiobook fan does

but with a careful, analytical ear

and flag the moments where the narration slips, so the underlying models can be made better.

This is remote, part-time work at roughly 20 hours per week (about 4 hours per day). You can be based anywhere, though we prefer people living in a region where Brazilian Portuguese is natively spoken.

2. What You'll Do • Listen to AI-narrated audiobooks in Brazilian Portuguese 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.

3. Who We're Looking For • Native or near-native fluency in Brazilian Portuguese, and an active, genuine audiobook listener

someone who listens regularly and has real opinions about what makes a good listen. • Enough working English to report clearly and communicate with the team (you do not need to be bilingual). • Some experience with annotation, labeling, transcription, proofreading, linguistics, or other detail-oriented review work. • A sharp, patient ear and the discipline to stay accurate over long listening sessions. • Reliable availability of about 20 hours per week on a part-time basis.

Nice to Have • Prior experience on AI training-data, model-evaluation, or audio/QA annotation projects. • A background in language, editing, voice, or audio production.