Education / school Evaluator

AI Trainer Jobs; United States; Remote; USD 110,000 - 165,000; Full time

Job summary

AuraOne seeks an experienced Education / school Evaluator to remotely review AI outputs across education workflows. You will assess tone, policy adherence, and stakeholder fit, flag risks, and document next steps to train the modeling team.

Responsibilities include grading against playbooks, capturing next steps, and adjudicating disputed calls with firm guidance. This is a remote, contractor role with flexible hours and asynchronous collaboration.

Qualifications

• Direct working experience in education review on real teams.
• Clear written reasoning that names the policy or workflow being applied.
• Reliable async availability for at least 10 hours per week.

Responsibilities

• Review AI outputs against current education review workflows, playbooks, and firm policy for Education / school Evaluator 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.

Skills

Operational review

Policy adherence

Workflow judgment

Stakeholder communication

Education review

Tools

AI tooling familiarity

Job description

Education / school Evaluator is a remote review track for evaluating AI outputs across education review workflows. Reviewers grade workflow correctness, policy adherence, and stakeholder fit; flag operational risk; and document the right next step so the modeling team can train on it.

Category: Education & Learning Evaluation · Pay: $80–$120 / hr · Location: Remote — US-eligible · Contractor

Education / school Evaluator is a remote review track for evaluating AI outputs across education review workflows.

Role details

About the role

Education / school Evaluator is a remote review track for evaluating AI outputs across education review workflows. Reviewers grade workflow correctness, policy adherence, and stakeholder fit; flag operational risk; and document the right next step so the modeling team can train on it.
Education review AI has to fit into an actual day at work. AuraOne uses experienced operators to grade outputs the way a senior peer would — checking workflow, policy, and the unwritten rules that decide whether a task actually gets done.
Review tutoring and assessment output. Judge it against how real learners use it.

Responsibilities

• Review AI outputs against current education review workflows, playbooks, and firm policy for Education / school Evaluator 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.

What you should bring

• Direct working experience in education review on real teams for Education / school Evaluator work.
• 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 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

• Grade a model's response to a real education review ticket and rate workflow, tone, and escalation.
• Flag a missed escalation with the right severity tag and corrected next step.
• Adjudicate a disputed playbook call between two reviewers using firm guidance.
• Audit a 25-row batch for rubric consistency and report drift to the program lead.

Useful experience

• Prior experience training, calibrating, or QA-ing operations teams.
• Familiarity with AI-assisted workflow tooling and its failure modes.
• Bilingual experience for cross-region operations.

Compensation and schedule

$80–$120 / 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

• Operational review
• Policy adherence
• Workflow judgment
• Stakeholder communication
• Education review