JavaScript and TypeScript AI Evaluator

About the role JavaScript and TypeScript AI Evaluator is a remote evaluation track for reviewing javascript and typescript ai 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 javascript and typescript ai 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 javascript and typescript ai evaluation model outputs against a versioned rubric and assign severity tags for JavaScript and TypeScript AI Evaluator 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. 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 javascript and typescript ai evaluation or adjacent content for JavaScript and TypeScript AI Evaluator 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 javascript and typescript ai 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 JavaScript and TypeScript AI evaluation Software engineering and computer use AI evaluation Rubric writing Expert review 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. #J-18808-Ljbffr AI Trainer Jobs