Remote Data Annotation Specialist — Part-Time (CAD 30/hr)

Dorado; United States; Remote; USD 24,317 - 34,634; Part time

Job summary

Cohere is seeking a Data Annotation Specialist to join our distributed team and help improve the quality of AI models through structured evaluation across text, image, and data formats.

As an independent contractor, you will work remotely from Canada for 16 hours per week at a CAD 30/hour rate, with a flexible schedule and strong emphasis on accuracy, guidelines, and edge-case detection in evolving tasks.

Qualifications

• 1+ years of experience in AI data annotation, LLM evaluation, content moderation, or related analytical role.
• Experience applying detailed guidelines to complex and ambiguous content with strong contextual judgment.
• Comfort with ambiguity and flagging edge cases rather than guessing.
• Excellent command of written English with ability to justify evaluations and provide clear prompts/exemplars.
• Familiarity with how large language models behave (e.g., hallucination, instruction-following gaps) is a plus.

Responsibilities

• Evaluate and rank model outputs, writing clear justifications for judgments.
• Stress-test and break models, documenting reproducible cases for engineers/researchers.
• Create datasets by authoring prompts, responses, and exemplars.
• Build rubrics and taxonomies, applying graded criteria consistently.
• Annotate and correct multimodal data across text, image, and structured formats.
• Calibrate and maintain consistency through inter-annotator checks.

Skills

AI data annotation

Guideline interpretation

Contextual judgment

Written English

Ambiguity tolerance

Tools

Annotation platforms

JSON

CSV/TSV

Markdown

XML

YAML

Job description

Cohere is seeking a Data Annotation Specialist to join our distributed team and help improve the quality of AI models through structured evaluation across text, image, and data formats.

As an independent contractor, you will work remotely from Canada for 16 hours per week at a CAD 30/hour rate, with a flexible schedule and strong emphasis on accuracy, guidelines, and edge-case detection in evolving tasks.