Hindi Language Expert (US/Canada Based)

AI Trainer Jobs; United States; Remote; USD 34,000 - 55,000; Part time

Job summary

AuraOne is seeking a Hindi Language Expert (US/Canada Based) to remotely review Hindi prompts and responses against our quality rubric. You will compare paired outputs, label edge cases, and write structured feedback for retraining.

As a contractor, you’ll evaluate frontier model outputs, judge benchmark failures, and calibrate fellow reviewers. Must have experience in Hindi evaluation or related content, with strong written reasoning and attention to detail.

Qualifications

• Experience evaluating Hindi generalist evaluation or related content.
• Clear written reasoning that names issues and rubric clauses.
• Ability to flag problematic prompts accurately.

Responsibilities

• Evaluate Hindi generalist outputs against a versioned rubric.
• Label edge cases with structured tags.
• Compare paired responses and select the stronger answer with rationale.
• Capture ambiguous prompts and route to rubric updates.
• Calibrate reviewer quality against gold-standard examples.

Skills

Model output evaluation

Rubric-based annotation

Severity tagging

Inter-rater calibration

Hindi generalist evaluation

Job description

Hindi Language Expert (US/Canada Based) is a remote evaluation track for reviewing hindi generalist evaluation prompts and responses against AuraOne's quality rubric. Reviewers compare paired outputs, label edge cases, and write the kind of structured feedback the modeling team can use to retrain.

Category: Frontier Model Evaluation · Pay: Hourly rate confirmed after the interview process · Location: Remote — US-eligible · Contractor

Hindi Language Expert (US/Canada Based) is a remote evaluation track for reviewing hindi generalist evaluation prompts and responses against AuraOne's quality rubric.

About the role

Hindi Language Expert (US/Canada Based) is a remote evaluation track for reviewing hindi generalist evaluation prompts and responses against AuraOne's quality rubric. Reviewers compare paired outputs, label edge cases, and write the kind of 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. Judge benchmark failures and calibrate other evaluators.

Responsibilities

• Evaluate hindi generalist evaluation model outputs against a versioned rubric and assign severity tags for Hindi Language Expert (US/Canada Based) 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.

Role details

Track Evaluation & annotation Work model Remote · Independent specialist contractor Compensation Hourly rate confirmed after the interview process. Eligible from US

What you should bring

• Prior evaluation, annotation, or human-rater experience on hindi generalist evaluation or adjacent content for Hindi Language Expert (US/Canada Based) work.
• 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.

Role signals

Example tasks

• Compare two hindi generalist evaluation model responses to the same prompt and pick the stronger one with rationale.
• Tag an unsafe response with the correct policy category and severity.
• Audit a 50-row batch for rubric consistency and report drift to the program lead.
• Propose a rubric clarification after spotting a recurring failure mode.

Useful experience

• Background in linguistics, content moderation, or trust & safety review.
• Experience with inter-rater agreement metrics and calibration cycles.
• Domain expertise that lets you spot subject-matter errors automated checks miss.

Compensation and schedule

Hourly rate confirmed after the interview process.
Expected arrangement: contractor , with program-defined task volume and review pacing. Placement depends on current program demand and reviewer confirmation.

Skills used in matching

• Model output evaluation
• Rubric-based annotation
• Severity tagging
• Inter-rater calibration
• Hindi generalist evaluation