AI Data Labeller (Text / NLP)

We're looking for an experienced text and NLP data labeller to help build high-quality training and evaluation datasets for our AI models. You'll work directly with raw text data, annotating, classifying, and quality-checking it against detailed guidelines so our models learn from accurate, consistent labels.

This is hands-on annotation work for someone who already knows the craft: you understand edge cases, you flag ambiguity instead of guessing, and you care about labeling consistency at scale. This is a remote, contract engagement with flexible hours and the potential for ongoing work based on quality and throughput.

What you'll do

What we're looking for

• Proven experience in data annotation, labeling, or linguistic QA (please share examples or the types of projects you've worked on)
• Strong reading comprehension and an eye for detail and nuance in written language
• Native or fluent English (additional languages a plus; specify which)
• Comfort working with annotation tools (e.g. Label Studio, Prodigy, Labelbox, or similar) and spreadsheets
• Ability to follow complex guidelines precisely and maintain consistency across long sessions
• Reliable internet, self-direction, and clear communication for a remote setup

Nice to have

• Background in linguistics, languages, journalism, content, or a related field
• Familiarity with NLP concepts (tokenization, NER, intent classification, RLHF / model evaluation)
• Experience rating or ranking AI-generated outputs (preference comparison, red-teaming)
• Prior remote freelance experience with distributed teams