English Voice Recording - Speech Data Collection

AuraOne, Inc.; United States; Remote; USD 34,000 - 55,000; Part time

Job summary

AuraOne, Inc. is seeking an independent contractor to perform English Voice Recording - Speech Data Collection evaluation tasks remotely. Review prompts and responses, label edge cases, and provide structured feedback to retrain models.

As a reviewer, compare paired outputs, apply the rubric, and document recurring failure modes. Reliable async availability for at least 10 hours per week is expected with high attention to detail.

Qualifications

• Experience in evaluation, annotation, or human-rater work on English voice recording evaluation tasks.
• Ability to apply multi-page rubrics consistently across large batches.
• Clear written reasoning that names the issue and rubric clause used.
• Attention to detail and ability to flag prompt-level problems.

Responsibilities

• Evaluate English voice recording evaluation model outputs against a versioned rubric and assign severity tags.
• Compare paired responses and select the stronger answer with rationale.
• Label hallucinations and unsafe content with structured tags.
• Capture ambiguous prompts and escalate to rubric updates.
• Calibrate reviewer scores against gold-standard examples weekly.
• Document recurring failure modes for future training.

Skills

Model output evaluation

Rubric-based annotation

Severity tagging

Inter-rater calibration

English Voice Recording evaluation

Tools

None

Job description

English Voice Recording - Speech Data Collection is a remote evaluation track for reviewing english voice recording 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.

Why this role matters

AI data reviewers help turn english voice recording evaluation outputs into auditable labels, rationales, and regression cases for AuraOne Human Data.

Responsibilities

• Evaluate english voice recording evaluation model outputs against a versioned rubric and assign severity tags for English Voice Recording - Speech Data Collection 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.
• Document recurring failure modes so the modeling team can target them in the next training run.

Qualifications

• Prior evaluation, annotation, or human-rater experience on english voice recording evaluation or adjacent content for English Voice Recording - Speech Data Collection 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.

Example tasks

• Compare two english voice recording 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.

Nice to have

• 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.

Skills

• Model output evaluation
• Rubric-based annotation
• Severity tagging
• Inter-rater calibration
• English Voice Recording evaluation

Work model

Remote — US-eligible. Remote · Independent specialist contractor. Employment type: CONTRACTOR. Applicants must be authorized to work from US.

Compensation

Hourly rate confirmed after the interview process.