AI Audio Data Annotator (TTS/LLM)

We are looking for experienced AI data annotators to label audio recordings from 11 sourced voices. The recordings will be used to train AI TTS and/or LLM-related systems, so annotation quality and consistency are extremely important.

Annotators will follow detailed written instructions and label audio files according to our internal guidelines. The work may include audio quality review, text/audio validation, issue flagging, metadata tagging, and consistency checks.

Responsibilities
Listen to audio recordings carefully.
Apply our annotation instructions accurately.
Label audio quality issues, mismatches, or other required categories.
Flag unclear, noisy, incomplete, or problematic recordings.
Add notes where required.
Maintain consistency across assigned voice files.
Complete rework when QA feedback is provided.
Requirements
Experience with AI data annotation, audio labeling, speech data, transcription QA, TTS data, or LLM evaluation.
Strong attention to detail.
Ability to follow precise instructions.
Comfortable working in an annotation platform.
Reliable communication and turnaround.
Native or fluent understanding of the target language.
Preferred Experience
TTS dataset annotation
Speech/audio QA
Voice data labeling
Label Studio, Labelbox, SuperAnnotate, or similar tools
Audio transcription or validation
Linguistic, pronunciation, or prosody review

Onboarding:
Selected candidates will complete a short onboarding annotation test before being assigned production work.