Hindi Bilingual Evaluator - Prompts & Rubrics Remote

AI Trainer Jobs; United States; Remote; USD 15,000 - 21,000; Part time

Job summary

AI Trainer Jobs seeks a Bilingual Writer - Hindi (India) for a remote evaluation track. You will review hindi prompts and responses against AuraOne's quality rubric, compare paired outputs, label edge cases, and write structured feedback the modeling team can use to retrain.

AI data reviewers help turn hindi generalist evaluation outputs into auditable labels, rationales, and regression cases for AuraOne Human Data. Review frontier model outputs and calibrate other evaluators as needed.

Qualifications

• Prior evaluation, annotation, or human-rater experience on hindi generalist evaluation or adjacent content.
• Comfort applying multi-page rubrics consistently across long batches.
• Clear written reasoning that names the issue and the rubric clause being applied.
• Strong attention to detail and the ability to flag when a prompt itself is the problem.
• Reliable async availability for at least 10 hours per week.

Responsibilities

• Evaluate hindi generalist evaluation model outputs against a versioned rubric and assign severity tags for Bilingual Writer - Hindi (India) 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.

Skills

Model output evaluation

Rubric-based annotation

Severity tagging

Inter-rater calibration

Hindi generalist evaluation

Job description

AI Trainer Jobs seeks a Bilingual Writer - Hindi (India) for a remote evaluation track. You will review hindi prompts and responses against AuraOne's quality rubric, compare paired outputs, label edge cases, and write structured feedback the modeling team can use to retrain.

AI data reviewers help turn hindi generalist evaluation outputs into auditable labels, rationales, and regression cases for AuraOne Human Data. Review frontier model outputs and calibrate other evaluators as needed.