Sanskrit Language Expert

AI Trainer Jobs; United States; Remote; USD 34,000 - 83,000; Part time

Benefits offered by this job

Remote work

Job summary

AuraOne is seeking a Sanskrit Language Expert for a remote evaluation track. You will review prompts and responses, label edge cases, and provide structured feedback to retrain the modeling system. The role focuses on auditability and quality scoring.

Responsibilities include comparing outputs, tagging issues, and calibrating scores weekly. This is a contractor, remote position with flexible hours and an hourly rate discussed after interview.

Qualifications

• Prior evaluation, annotation, or human-rater experience on Sanskrit language evaluation or adjacent content.
• Clear written reasoning that names the issue and the rubric clause being applied.
• Strong attention to detail and ability to flag when a prompt itself is the problem.

Responsibilities

• Evaluate Sanskrit language evaluation model outputs against a versioned rubric and assign severity tags.
• 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

Sanskrit evaluation

Annotation experience

Clear written reasoning

Attention to detail

Async availability

Job description

Role details

Sanskrit Language Expert is a remote evaluation track for reviewing sanskrit 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.

About the role

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