Remote Imagery AI/ML Training Data Reviewer

AuraOne, Inc.; United States; Remote; USD 34,000 - 69,000; Full time

Job summary

AuraOne, Inc. is seeking a remote Imagery Analyst for AI/ML Training Data work. This independent contractor role requires reviewing outputs, applying rubrics, and documenting policy-driven reasoning. Candidates should be able to work asynchronously for at least 10 hours weekly and align with US-eligible remote operations.

The position emphasizes policy adherence, meticulous review, and clear communication to support the modeling team’s training data improvements.

Qualifications

• Direct working experience in imagery analyst AI/ML training data operations.
• Ability to apply multi-page rubrics consistently.
• Clear written reasoning naming the policy or workflow applied.
• Strong attention to detail and ability to flag prompt issues.
• Reliable async availability for at least 10 hours per week.

Responsibilities

• Review AI outputs against workflows, playbooks, and firm policy for Imagery Analyst - AI/ML Training Data 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

Imagery analyst operations

Attention to detail

Policy adherence

Async availability

Reasoning and documentation

Job description

AuraOne, Inc. is seeking a remote Imagery Analyst for AI/ML Training Data work. This independent contractor role requires reviewing outputs, applying rubrics, and documenting policy-driven reasoning. Candidates should be able to work asynchronously for at least 10 hours weekly and align with US-eligible remote operations.

The position emphasizes policy adherence, meticulous review, and clear communication to support the modeling team’s training data improvements.