Remote Language Learning Content Reviewer - AI QA & Policy

AuraOne; United States; On-site; USD 34,440,000 - 61,992,000; Full time

Job summary

AuraOne is seeking a Language Learning Content Reviewer for a remote contractor role focused on evaluating AI outputs within language learning content operations. You will assess workflow accuracy, policy adherence, and appropriate escalation, helping ensure reliable data for model training.

Candidates should have hands-on experience with language learning content operations, be able to apply multi-page rubrics, and communicate clearly about which policy or workflow is used.

Qualifications

• Direct experience in language learning content reviewer operations on real teams.
• Comfort applying multi-page rubrics consistently across long batches.
• Clear written reasoning that names the policy or workflow being applied.
• Strong attention to detail and ability to flag when a prompt is the problem.
• Reliable async availability for at least 10 hours per week.

Responsibilities

• Review AI outputs against current language learning content workflows, playbooks, and firm policy for Reviewer assignments.
• Grade tone, escalation logic, and stakeholder fit on a structured rubric.
• Flag operational risk, missed escalations, and policy-adherence gaps with severity tags.
• Capture the right next step so the modeling team can train on it.
• Adjudicate disputed treatments against published playbooks or firm guidance.
• Maintain reviewer-quality scores in inter-rater calibration cycles.

Skills

Operational review

Policy adherence

Workflow judgment

Stakeholder communication

Job description

AuraOne is seeking a Language Learning Content Reviewer for a remote contractor role focused on evaluating AI outputs within language learning content operations. You will assess workflow accuracy, policy adherence, and appropriate escalation, helping ensure reliable data for model training.

Candidates should have hands-on experience with language learning content operations, be able to apply multi-page rubrics, and communicate clearly about which policy or workflow is used.