Persian Language Expert

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

Job summary

AI Trainer Jobs is seeking a Persian Language Expert for a remote evaluation track. Review prompts and responses against AuraOne's quality rubric, compare paired outputs, label edge cases, and provide structured feedback for retraining.

Responsibilities include evaluating model outputs, tagging issues with severity, and calibrating against gold-standard examples on a weekly cadence. Strong written reasoning is required.

Qualifications

• Experience evaluating Persian language content against rubrics.
• Ability to apply long multi-page rubrics consistently.
• Clear written reasoning naming issues and rubric clauses.

Responsibilities

• Evaluate Persian language evaluation model outputs against a versioned rubric and assign severity tags.
• Compare paired responses and select the stronger answer with rationale.
• Label unsafe content and policy violations with structured tags.
• Capture ambiguous prompts and route to program team for rubric updates.
• Calibrate reviewer scores against gold-standard examples weekly.

Skills

Persian language evaluation

Annotation

Rubric-based annotation

Inter-rater calibration

Attention to detail

Async work

Job description

Persian Language Expert is a remote evaluation track for reviewing persian language 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

Persian Language Expert is a remote evaluation track for reviewing persian language evaluation prompts and responses against AuraOne's quality rubric.

Role details

About the role

Persian Language Expert is a remote evaluation track for reviewing persian language 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 persian language 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 persian language evaluation model outputs against a versioned rubric and assign severity tags for Persian Language Expert 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.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 persian language evaluation or adjacent content for Persian Language Expert 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 persian language 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
• Persian Language evaluation

Application boundary

Creating a specialist profile records your experience and preferences. Starting role intake is a separate action that attaches this role to your candidate record.

Specialist intake

The intake preserves your chosen role, the visible terms, and source attribution for reviewer context.
- 01 Confirm profile and eligibility details.
- 02 Attach this role deliberately.
- 03 Receive a human review decision or follow-up.
Placement timing depends on program demand and reviewer confirmation.