Remote French LLM Quality & Data Linguist

Mercor

Paris

Sur place

EUR 42 000 - 70 000

Plein temps

14 jours+
Générateur de candidature

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Résumé du poste

Mercor is seeking experienced French Linguistic Experts to join a cutting-edge AI research project in partnership with a leading research lab. This role focuses on evaluating how well a large language model performs in French tasks and on curating high-quality French linguistic data to train and improve the model’s understanding and generation.

You will edit and refine French content, annotate linguistic features, identify model errors, and collaborate with AI researchers to drive improvements.

Qualifications

  • Native or near-native fluency in French (grammar, syntax, style).
  • Experience in translation, editing, linguistic annotation, or NLP data work in French.
  • Strong understanding of linguistic nuances and regional variations.
  • Interest in AI and LLM-driven language technologies (preferred).
  • Excellent attention to detail and ability to spot subtle errors or unnatural phrasing.

Responsabilités

  • Evaluate the quality and accuracy of LLM-generated French text across use cases.
  • Edit, refine, or rewrite French content to meet linguistic and cultural standards.
  • Annotate French text for grammatical, syntactic, and semantic features.
  • Identify model errors and language gaps, and collaborate with AI researchers to improve LLM performance.
  • Provide detailed linguistic feedback to guide ongoing model training.

Connaissances

French fluency
Linguistic annotation
Editing & translation
NLP data work
Attention to detail

Description du poste

Mercor is seeking experienced French Linguistic Experts to join a cutting-edge AI research project in partnership with a leading research lab. This role focuses on evaluating how well a large language model performs in French tasks and on curating high-quality French linguistic data to train and improve the model’s understanding and generation.

You will edit and refine French content, annotate linguistic features, identify model errors, and collaborate with AI researchers to drive improvements.

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