Data-Video Generalist - LATAM

AI Trainer Jobs; United States; Remote; USD 28,000 - 55,000; Full time

Job summary

AuraOne is seeking a Data-Video Generalist for LATAM to review prompts and responses against an in-house rubric. You will evaluate outputs, label edge cases, and provide structured feedback to retrain models, ensuring alignment with quality standards.

The role focuses on reviewing paired outputs, labeling issues, and contributing to rubric calibration. This is a remote contractor position with an hourly rate to be confirmed after interview, eligible for US-based contractors.

Qualifications

• Experience in data-video evaluation or related content moderation.
• Ability to apply rubrics consistently across long batches.
• Clear written reasoning naming the issue and rubric clause.

Responsibilities

• Evaluate data-video generalist LATAM outputs against a versioned rubric and assign severity tags.
• Compare paired responses and select the stronger answer with a rationale.
• Label hallucinations, instruction-following failures, and unsafe content with structured tags.
• Capture ambiguous prompts and route to the program team for rubric updates.
• Calibrate reviewer quality against gold-standard examples weekly.

Job description

Data-Video Generalist - LATAM is a remote evaluation track for reviewing data video generalist latam evaluation prompts and responses against AuraOne's quality rubric. Reviewers compare paired outputs, label edge cases, and write the kind of structured feedback the modeling team can use to retrain.

Category: Video, Vision & Spatial AI · Pay: Hourly rate confirmed after the interview process · Location: Remote — US-eligible · Contractor

Data-Video Generalist - LATAM is a remote evaluation track for reviewing data video generalist latam evaluation prompts and responses against AuraOne's quality rubric.

About the role

Data-Video Generalist - LATAM is a remote evaluation track for reviewing data video generalist latam evaluation prompts and responses against AuraOne's quality rubric. Reviewers compare paired outputs, label edge cases, and write the kind of structured feedback the modeling team can use to retrain.
AI data reviewers help turn data video generalist latam evaluation outputs into auditable labels, rationales, and regression cases for AuraOne Human Data.
Review image and video output. Judge spatial reasoning and scene understanding.

Responsibilities

• Evaluate data video generalist latam evaluation model outputs against a versioned rubric and assign severity tags for Data-Video Generalist - LATAM assignments.
• 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.

Role details

Track Evaluation & annotation Work model Remote · Independent specialist contractor Compensation Hourly rate confirmed after the interview process. Eligible from US

What you should bring

• Prior evaluation, annotation, or human-rater experience on data video generalist latam evaluation or adjacent content for Data-Video Generalist - LATAM work.
• 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.

Role signals

Example tasks

• Compare two data video generalist latam evaluation model responses to the same prompt and pick the stronger one with rationale.
• Tag an unsafe response with the correct policy category and severity.
• Audit a 50-row batch for rubric consistency and report drift to the program lead.
• Propose a rubric clarification after spotting a recurring failure mode.

Useful experience

• Background in linguistics, content moderation, or trust & safety review.
• Experience with inter-rater agreement metrics and calibration cycles.
• Domain expertise that lets you spot subject-matter errors automated checks miss.

Compensation and schedule

Hourly rate confirmed after the interview process.
Expected arrangement: contractor , with program-defined task volume and review pacing. Placement depends on current program demand and reviewer confirmation.

Skills used in matching

• Model output evaluation
• Rubric-based annotation
• Severity tagging
• Inter-rater calibration
• Data Video Generalist LATAM evaluation
• Design