Linguistics Expert – AI Training & Content Writing (German)

Innodata Inc.; Deutschland; Vor Ort; EUR 45.000 - 75.000; Vollzeit

Zusammenfassung

Innodata Inc. seeks a Linguistics Expert to support AI training and content writing, shaping language model capabilities through high-quality linguistic data curation and annotation.

The role focuses on creating grammar guides, analyses, and examples, while assessing model outputs for fluency and accuracy. A strong linguistics background and interest in NLP are essential for success.

Qualifikationen

• Master's degree in Linguistics or a related field.
• Strong analytical abilities with attention to detail.
• Experience with NLP data or linguistic annotation is a plus.

Aufgaben

• 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, tone, and accuracy.
• Support research by summarizing linguistic findings for internal teams.

Kenntnisse

Linguistic analysis

Data curation

Content writing

NLP knowledge

Ausbildung

Master's degree in Linguistics

Jobbeschreibung

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.