Telugu Language Expert

AI Trainer Jobs; United States; Remote; USD 28,000 - 55,000; Full time

Job summary

AuraOne seeks a Telugu Language Expert to remotely evaluate model outputs against a versioned rubric. You will tag severity, compare paired responses, and provide structured feedback to retrain prompts. Prior Telugu evaluation experience is required, with careful, documented reasoning across long task batches.

This is a remote contractor role in the United States with program-defined task volume and weekly calibration to maintain reviewer quality.

Qualifications

• Prior evaluation, annotation, or human-rater experience on Telugu language evaluation or adjacent content.
• Ability to apply multi-page rubrics consistently across long batches.
• Clear written reasoning that names the issue and rubric clause.

Responsibilities

• Evaluate Telugu language evaluation model outputs against a versioned rubric and tag severity.
• Compare paired responses and select the stronger one with rationale.
• Label edge cases, hallucinations, instruction-following failures, and unsafe content.
• Capture ambiguous prompts and flag for rubric updates.
• Calibrate reviewer-quality scores against gold-standard examples weekly.

Skills

Telugu language evaluation experience

Attention to detail

Clear written reasoning

Inter-rater calibration

Job description

Telugu Language Expert is a remote evaluation track for reviewing telugu 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

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

Role details

About the role

Telugu Language Expert is a remote evaluation track for reviewing telugu language evaluation prompts and responses against AuraOne's quality rubric.
AI data reviewers help turn telugu 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 telugu language evaluation model outputs against a versioned rubric and assign severity tags for Telugu 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.

What you should bring

• Prior evaluation, annotation, or human-rater experience on telugu language evaluation or adjacent content for Telugu 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 telugu 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
• Telugu Language evaluation