Quality Engineering Specialist (Remote) AI Reviewer

AuraOne, Inc.

United States

A distancia

USD 55.000 - 96.000

Jornada completa

14 días+

Una candidatura completa en un minuto

Currículum y carta de presentación personalizados, listos para enviar.

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Descripción de la vacante

AuraOne, Inc. is seeking a remote Member of Technical Staff, Quality Engineering specialist operations contractor to review AI outputs and ensure alignment with workflows and policies.

You will evaluate tone, escalation paths, and stakeholder fit on structured rubrics. You will document actionable next steps to help the modeling team improve training data, flag operational risks, and drive consistent quality across long batches.

Formación

  • Direct working experience in member of technical staff quality engineering specialist operations on real teams.
  • Ability to apply multi-page rubrics consistently across long batches.
  • Clear written reasoning naming the policy or workflow being applied.
  • Strong attention to detail and ability to flag when a prompt itself is the problem.
  • Reliable async availability for at least 10 hours per week.

Responsabilidades

  • Review AI outputs against workflows, playbooks, and firm policy for MTS, QE 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.

Conocimientos

Operational review
Policy adherence
Workflow judgment
Stakeholder communication
MTS QE ops

Descripción del empleo

AuraOne, Inc. is seeking a remote Member of Technical Staff, Quality Engineering specialist operations contractor to review AI outputs and ensure alignment with workflows and policies.

You will evaluate tone, escalation paths, and stakeholder fit on structured rubrics. You will document actionable next steps to help the modeling team improve training data, flag operational risks, and drive consistent quality across long batches.

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