Academic Search Research QA Specialist

AI Trainer Jobs; United States; Remote; USD 41,000 - 83,000; Part time

Job summary

AI Trainer Jobs is seeking an Academic Search Research QA Specialist for remote evaluation work. You will assess prompts and responses against AuraOne's rubric, label edge cases, and provide structured feedback to retrain models.

This is a contractor, remote role with US-eligible status, requiring about 10 hours per week to start and strong attention to detail. Responsibilities include evaluating outputs, selecting stronger answers with rationale, tagging content, and surfacing rubric gaps for

Qualifications

• Prior evaluation, annotation, or human-rater experience in academic search QA.
• Ability to apply multi-page rubrics consistently.
• Clear written reasoning naming the issue and rubric clause.
• Reliable async availability for at least 10 hours per week.

Responsibilities

• Evaluate model outputs against rubric and assign severity tags.
• Compare paired responses and justify the stronger answer.
• Label hallucinations and unsafe content with structured tags.
• Capture ambiguous prompts and route for rubric updates.

Skills

Evaluation

Annotation

Inter-rater calibration

Rubric annotation

Severity tagging

Source grounding

Web research

Browser automation

Academic search QA

Attention to detail

Tools

Browser automation

Job description

Academic Search Research QA Specialist is a remote evaluation track for reviewing academic search research qa 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: Search, Web & Browser Agents · Pay: $30–$60 / hr · Location: Remote — US-eligible · Contractor

Academic Search Research QA Specialist is a remote evaluation track for reviewing academic search research qa evaluation prompts and responses against AuraOne's quality rubric.

About the role

Academic Search Research QA Specialist is a remote evaluation track for reviewing academic search research qa evaluation prompts and responses against AuraOne's quality rubric.
AI data reviewers help turn academic search research qa evaluation outputs into auditable labels, rationales, and regression cases for AuraOne Human Data.
Review browser automation and multi-step search agents. Check whether sources hold up.

Responsibilities

• Evaluate academic search research qa evaluation model outputs against a versioned rubric and assign severity tags for Academic Search Research QA Specialist 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.

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 academic search research qa evaluation or adjacent content for Academic Search Research QA Specialist 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 academic search research qa 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
• Academic Search Research QA evaluation
• Web research
• Source grounding
• Browser automation
• Academic
• Search

Application boundary

Creating a specialist profile records your experience and preferences. Starting role intake is a separate action that attaches this role to your candidate record.

Specialist intake

The intake preserves your chosen role, the visible terms, and source attribution for reviewer context.

• 01 Confirm profile and eligibility details.
• 02 Attach this role deliberately.
• 03 Receive a human review decision or follow-up.

Placement timing depends on program demand and reviewer confirmation.