French TTS Audio Quality Engineer

Mercor; Zürich; Remote; CHF 70.000 - 90.000; Vollzeit

Zusammenfassung

Mercor is seeking an audio engineer to edit and quality-check French voice recordings for speech and text-to-speech (TTS) applications. You will ensure clarity, consistency, and technical compliance across large volumes of French data.

You will apply audio cleanup, silence trimming, noise reduction, and QA checks against strict specifications for ML training pipelines, collaborating with teams across speech datasets and model training workflows.

Qualifikationen

• Native French speaker with strong listening intuition for French speech nuances.
• Experience editing speech or voice recordings (not music).
• Knowledge of speech audio quality standards and common issues in dialogue.
• Hands-on with iZotope RX, Pro Tools, or similar restoration software.
• Ability to fix artifacts and defects in audio and manage large datasets.

Aufgaben

• Edit and process French voice recordings for TTS and speech AI systems.
• Perform audio cleanup including silence trimming, noise reduction, and de-clicking.
• Conduct QA checks for clipping, background noise, and loudness consistency.
• Ensure audio meets strict technical specifications for ML pipelines.
• Evaluate pronunciation accuracy, naturalness, and fluency in French.
• Work with large batches of recordings maintaining consistency and throughput.
• Collaborate with teams on French speech datasets, talent recordings, and model training workflows.

Kenntnisse

Native French speaker

Speech editing

Audio quality standards

Critical listening

High-volume data handling

Tools

iZotope RX

Pro Tools

Jobbeschreibung

Mercor is seeking an audio engineer to edit and quality-check French voice recordings for speech and text-to-speech (TTS) applications. You will ensure clarity, consistency, and technical compliance across large volumes of French data.

You will apply audio cleanup, silence trimming, noise reduction, and QA checks against strict specifications for ML training pipelines, collaborating with teams across speech datasets and model training workflows.