Generalist - English & Telugu
Quick facts
- Pay
- $15–20 / hour
- Type
- Contract
- Location
- Remote — US-eligible
- Hours
- 10+ hours / week
- Languages
- Telugu
- Platform
- Aura One — 3510 open jobs
- Typical pay at Aura One
- $20–150/hour · median $80 (1547 jobs on our site)
- Apply
- Free to apply — never pay to get AI training work
About the role
Generalist - English & Telugu is a remote evaluation track for reviewing generalist english telugu 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 generalist english telugu 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 generalist english telugu evaluation model outputs against a versioned rubric and assign severity tags for Generalist - English & Telugu 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 generalist english telugu evaluation or adjacent content for Generalist - English & Telugu 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 generalist english telugu 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
$15–$20 / hr
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
- Generalist English Telugu 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.
About Aura One
AuraOne runs a human-data job board where AI labs hire professionals to evaluate and train models. Listings range from entry-level AI evaluation specialists to registered nurses, administrative professionals and scenario designers.