Remote Dutch Linguistic Expert for AI Research (Part-Time)

Mercor; United States; Remote; USD 45,000 - 65,000; Part time

Job summary

Mercor seeks experienced Dutch Linguistic Experts to contribute to a cutting-edge AI research project. The role focuses on evaluating LLM Dutch tasks and curating high-quality Dutch data to train and improve model understanding and generation.

You will assess translations, summaries, dialogues, and grammar, edit Dutch content for cultural and linguistic accuracy, and annotate text to guide researchers in model training. This is a remote, part-time engagement appealing to detail-driven linguists.

Qualifications

• Native or near-native fluency in Dutch.
• Experience in translation, editing, linguistic annotation, or NLP data work.
• Strong understanding of Dutch nuances, regional variations, register and context.
• Professional fluency in English.
• Interest in AI and LLM language technologies (preferred).

Responsibilities

• Evaluate the quality and accuracy of LLM-generated Dutch text across use cases (translation, summarization, dialogue, grammar correction).
• Edit, refine, or rewrite Dutch content to meet linguistic and cultural standards for Dutch-speaking audiences.
• Annotate Dutch 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 and analysis to guide ongoing model training efforts.

Skills

Dutch fluency

English fluency

Attention to detail

Remote collaboration

Job description

Mercor seeks experienced Dutch Linguistic Experts to contribute to a cutting-edge AI research project. The role focuses on evaluating LLM Dutch tasks and curating high-quality Dutch data to train and improve model understanding and generation.

You will assess translations, summaries, dialogues, and grammar, edit Dutch content for cultural and linguistic accuracy, and annotate text to guide researchers in model training. This is a remote, part-time engagement appealing to detail-driven linguists.