French Speech Audio Engineer

Mercor; Paris; Sur place; EUR 45 000 - 65 000; Plein temps

Résumé du poste

Mercor is seeking an audio engineer to edit and quality-check French voice recordings for TTS and speech AI applications. You will process large datasets, ensure audio clarity and consistency, and maintain strict technical standards for ML pipelines.

The ideal candidate is a native or near-native French speaker with experience editing speech recordings and strong knowledge of audio quality standards. Proficiency with iZotope RX or Pro Tools is required, and you will handle high-volume datasets

Qualifications

• Native or near-native French speaker with strong listening intuition.
• Experience editing speech or voice recordings (not music).
• Strong understanding of speech audio quality standards and common issues in dialogue.
• Hands-on experience with iZotope RX, Pro Tools, or similar tools.

Responsabilités

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

Connaissances

Native French speaker

Speech editing

Audio QA knowledge

Attention to detail

Outils

iZotope RX

Pro Tools

Description du poste

OverviewWe're looking for audio engineers with strong experience editing and quality-checking voice recordings for speech and text-to-speech (TTS) applications, specifically for French-language audio. This role focuses on preparing high-quality audio datasets for machine learning systems, ensuring clarity, consistency, and technical compliance across large volumes of French speech data. Native or near-native French fluency is required to accurately assess speech quality, pronunciation, and naturalness.

What You'll Do

• Edit and process French voice recordings for use in TTS and speech AI systems

• Perform audio cleanup including silence trimming, breath reduction/removal, de-clicking, de-essing, and noise reduction

• Conduct detailed quality assurance checks for:

  • Clipping and distortion

  • Background noise and artifacts

  • Loudness consistency and level balancing

• Ensure audio meets strict technical specifications for ML training pipelines

• Evaluate recordings for French pronunciation accuracy, naturalness, and fluency

• Work with large batches of recordings, maintaining consistency and throughput

• Collaborate with teams working on French speech datasets, voice talent recordings, and model training workflows

Basic Qualifications

• Native or near-native French speaker with strong listening intuition for French speech nuances

• Experience editing speech or voice recordings (not just music production)

• Strong understanding of speech audio quality standards and common issues in recorded dialogue

• Hands-on experience with tools like iZotope RX, Pro Tools, or similar audio restoration software

• Ability to identify and fix artifacts, inconsistencies, and technical defects in audio

• Experience working with high-volume audio datasets or structured workflows

Preferred Qualifications

• Experience working with TTS vendors or platforms

• Prior involvement in speech ML, voice AI, or dataset creation/annotation workflows

• Familiarity with audio QA pipelines, labeling, or evaluation processes

• Experience directing or editing French voice talent recordings

Ideal Candidate Profile

• Detail-oriented with strong critical listening skills in French

• Comfortable working with repetitive, high-precision tasks at scale

• Able to balance speed and quality in production environments

• Familiar with the nuances of human French speech vs synthetic voice requirements