Linguistics Expert – AI Training & Content Writing

Innodata Inc.; France; Sur place; EUR 52 000 - 70 000; Plein temps

Résumé du poste

Innodata Inc in France is seeking a highly analytical linguist to support AI training and content writing. You will curate and annotate linguistic data, improve NLP pipelines, and contribute to model evaluation.

The role requires a strong academic background in linguistics (syntax, semantics, pragmatics, morphology, phonology, sociolinguistics) and a passion for language technology, clear communication, and high-quality QA.

Qualifications

• Advanced degree in linguistics or related field.
• Experience with annotation and data curation for NLP/LLMs.
• Strong analytical and written communication skills.

Responsabilités

• Create or edit linguistically rich content for NLP pipelines.
• Annotate linguistic datasets with syntactic, semantic, or pragmatic labels.
• Perform QA on model outputs for fluency and factual accuracy.
• Identify bias and ambiguity issues and propose improvements.
• Summarize linguistic research for internal teams.

Connaissances

Linguistics knowledge

Analytical mindset

Attention to detail

Formation

Advanced degree in linguistics

Description du poste

We are seeking a highly analytical and detail-oriented linguist to support AI training initiatives and linguistic content creation. This role is ideal for someone with a strong academic background in linguistics (syntax, semantics, pragmatics, morphology, phonology, sociolinguistics, etc.) and a passion for language, technology, and clear communication. You will play a crucial role in shaping the capabilities of large language models (LLMs) and NLP-based systems through high-quality linguistic data curation, annotation, and evaluation.

Job Title: Linguistics Expert – AI Training & Content Writing

Key Responsibilities:

• Create or edit linguistically- rich content including grammar guides, syntactic analyses, usage explanations, or examples for NLP pipelines.
• Identify and resolve issues related to ambiguity, bias, and grammaticality.
• Perform quality assurance (QA) on model outputs for fluency, tone, factual accuracy, and language appropriateness.
• Annotate linguistic datasets with syntactic, semantic, or pragmatic labels.
• Support internal teams by conducting linguistic research and summarizing findings.
• Apply linguistic knowledge to evaluate model behavior, error patterns, and generalization issues.