Arabic AI Evaluation & Annotation Specialist (Remote, Contractor)

AuraOne, Inc.; United States; Remote; USD 57,000 - 81,000; Full time

Job summary

AuraOne, Inc. is seeking an Arabic Linguistic Expert for AI Evaluation and Annotation (Remote). You will review Arabic outputs, label edge cases, and provide structured feedback to retrain models.

This is a remote contractor role requiring clear reasoning and high accuracy. Responsibilities include comparing responses, tagging safety issues, and maintaining calibration against gold-standard examples. Eligible candidates will have prior evaluation experience and reliable async availability for at

Qualifications

• Experience evaluating Arabic outputs against rubrics.
• Ability to apply multiple rubric criteria consistently.
• Strong written reasoning to name issues and rubric clauses.
• Attention to detail and prompt-issue identification.

Responsibilities

• Evaluate arabic generalist evaluation model outputs against a versioned rubric and assign severity tags for Arabic Linguistic Expert — AI Evaluation and Annotation (Remote) assignments.
• Compare paired responses and pick the stronger answer with a written rationale.
• Label hallucinations, instruction-following failures, and unsafe content with structured tags.
• Capture ambiguous prompts and route them back to the program team for rubric updates.
• Maintain reviewer-quality scores by calibrating against gold-standard examples each week.
• Document recurring failure modes so the modeling team can target them in the next training run.

Skills

Model output evaluation

Rubric-based annotation

Severity tagging

Inter-rater calibration

Arabic generalist evaluation

Job description

AuraOne, Inc. is seeking an Arabic Linguistic Expert for AI Evaluation and Annotation (Remote). You will review Arabic outputs, label edge cases, and provide structured feedback to retrain models.

This is a remote contractor role requiring clear reasoning and high accuracy. Responsibilities include comparing responses, tagging safety issues, and maintaining calibration against gold-standard examples. Eligible candidates will have prior evaluation experience and reliable async availability for at