Adversarial Prompt Expert
Remote AI evaluation role reviewing AI evaluation, annotation, and model review tasks for AuraOne AI Labs.
Fellowship · Feb 11—Dec 30 · Remote | Part-time AI Labs fellowship · Model evaluation
AI Evaluation & Annotation
Remote AI evaluation role reviewing audio and voice tasks for AuraOne AI Labs.
Remote AI evaluation role reviewing audio and voice tasks for AuraOne AI Labs. High-quality AI systems need consistent human judgment, clear rubrics, and reviewers who can turn edge cases into better training signal.
Review model outputs, label edge cases, and improve training quality across high-volume AI workflows.
We review domain depth, writing quality, and remote execution readiness before routing applicants into the final review queue.
Comp band stays visible through routing and review.
Built for remote specialist delivery from the start.
Aligned to the AuraOne specialist network.
AuraOne uses a shared intake to confirm track fit, review readiness, and the best queue for your specialist profile.
One specialist application captures background, availability, and evidence.
This role belongs to the AI Evaluation & Annotation track, so reviewers prioritize domain fluency, structured judgment, and the ability to operate asynchronously.
Reviewers weigh track alignment, written-judgment quality, and availability in concert. The list below expands on the compact aside at the top of the page.
If this role is close but not perfect, keep momentum by scanning adjacent openings in the same specialist lane.
Remote AI evaluation role reviewing AI evaluation, annotation, and model review tasks for AuraOne AI Labs.
Fellowship · Feb 11—Dec 30 · Remote | Part-time AI Labs fellowship · Model evaluation
Remote AI evaluation role reviewing AI evaluation, annotation, and model review tasks for AuraOne AI Labs.
$35 hourly · Remote | Flexible contract review work · Model evaluation
Remote AI evaluation role reviewing audio and voice tasks for AuraOne AI Labs.
$50 hourly · Remote | Flexible contract review work · Model evaluation