Remote English Linguistic Expert for AI Training

Mercor; San Jose (CA); On-site; USD 60,000 - 100,000; Full time

Benefits offered by this job

Fully remote

Flexible hours

Asynchronous work

Exposure to AI research

Job summary

Mercor is seeking experienced English Linguistic Experts to join a cutting-edge AI research project. You will evaluate how well a large language model performs on English tasks and curate high-quality English linguistic data to train and improve model understanding and generation.

You will edit, refine, and annotate English content, identify language gaps, and provide detailed linguistic feedback to guide continued model training. Fully remote with flexible, asynchronous hours.

Qualifications

• Native or near-native English with strong grammar, syntax, and style.
• Experience editing, proofreading, linguistic annotation, or NLP data work in English.
• Strong understanding of linguistic nuances, regional variations, tone, and context-appropriate usage.
• Excellent attention to detail and written communication skills.

Responsibilities

• Evaluate the quality and accuracy of LLM-generated English text across use cases (summarization, dialogue, grammar correction, rewriting, reasoning).
• Edit, refine, or rewrite English content to meet high linguistic and stylistic standards.
• Annotate English text for grammatical, syntactic, semantic, and stylistic features.
• Identify model errors and provide feedback to improve LLM performance.
• Provide detailed linguistic feedback to guide model training efforts.

Skills

English fluency

Editing

Proofreading

Linguistic annotation

NLP data work

Language evaluation

Independent work

Job description

Mercor is seeking experienced English Linguistic Experts to join a cutting-edge AI research project. You will evaluate how well a large language model performs on English tasks and curate high-quality English linguistic data to train and improve model understanding and generation.

You will edit, refine, and annotate English content, identify language gaps, and provide detailed linguistic feedback to guide continued model training. Fully remote with flexible, asynchronous hours.