Remote Image-Text Grounding QA Specialist

AuraOne; United States; On-site; USD 30,307 - 55,104; Full time

Job summary

AuraOne is seeking an Image-Text Grounding Dataset QA Specialist for a remote contractor role. You will review prompts and model outputs, apply the quality rubric, and provide structured feedback to retrain the system.

You will compare responses, label edge cases, and document recurring issues to help improve future training. This position requires at least 10 hours/week, strong attention to detail, and clear written reasoning.

Qualifications

• Prior evaluation, annotation, or human-rater experience on image text grounding dataset qa evaluation or adjacent content.
• Comfort applying multi-page rubrics consistently across long batches.
• Clear written reasoning that names the issue and the rubric clause 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.

Responsibilities

• Evaluate image text grounding dataset qa evaluation model outputs against a versioned rubric and assign severity tags.
• Compare paired responses and pick the stronger answer with a written rationale.
• Label hallucinations, instruction-following failures, and unsafe content with structured tags.
• Capture ambiguous prompts and route them back to the program team for rubric updates.
• Maintain reviewer-quality scores by calibrating against gold-standard examples each week.
• Document recurring failure modes so the modeling team can target them in the next training run.

Skills

Model output evaluation

Rubric-based annotation

Severity tagging

Inter-rater calibration

Multimodal evaluation

Education

Background in linguistics, content moderation, or trust & safety review

Job description

AuraOne is seeking an Image-Text Grounding Dataset QA Specialist for a remote contractor role. You will review prompts and model outputs, apply the quality rubric, and provide structured feedback to retrain the system.

You will compare responses, label edge cases, and document recurring issues to help improve future training. This position requires at least 10 hours/week, strong attention to detail, and clear written reasoning.