micro1
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RemoteHot

Research Evaluation Specialist (PhD or Masters / Researcher / Professor)

30–60/hr
Remote
Posted October 21, 2026
contract
20 openings
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Listing checked October 21, 2026 · pay as published by micro1

Overview

micro1 seeks Research Evaluation Specialists with a PhD or Masters to build rigorous test material for advanced AI model evaluation on a customer project. You will craft original, high-difficulty question-and-answer pairs at the frontier of your discipline, then verify and document answers using primary sources and authoritative references. The role is remote and worldwide, about 15 hours per week, with output-based pay. Prior experience in AI training, data labeling, or model evaluation is required.

What You'll Do6

  • 1Compose original, high-difficulty question-and-answer pairs that rigorously test AI model capabilities at the cutting edge of your field.
  • 2Source, verify, and thoroughly document answers using primary sources and authoritative references, including clear citations and reasoning.
  • 3Design questions that demand advanced reasoning, methodological nuance, or synthesis across multiple sources, ensuring resistance to oversimplified or shortcut solutions.
  • 4Test questions against AI systems, identify items that are not sufficiently challenging, and iteratively increase complexity while maintaining accuracy.
  • 5Write each question and answer with high precision and clarity, eliminating ambiguity and supporting defensible responses.
  • 6Integrate reviewer feedback and consistently uphold all project guidelines and quality standards throughout your deliverables.

Requirements7

  • 1Masters or PhD completed, active candidacy, or equivalent research experience as a specialist, researcher, assistant professor, or professor in your domain.
  • 2Demonstrated track record of scholarly research, in-depth subject matter expertise, and familiarity with primary literature.
  • 3Exceptional analytical thinking, close attention to detail, and strong written communication skills in English.
  • 4Experience sourcing and triangulating information from authoritative references.
  • 5Proven self-direction and reliability in delivering expert-level work independently within remote engagements.
  • 6Skill in composing challenging, original, and methodologically sound questions.
  • 7Prior experience in AI training, data labeling, or model evaluation is required.

Who Should Apply

The ideal candidate holds a PhD or Masters (or equivalent research experience) and has a strong publication or research record in their field. They have hands-on experience with AI training, data labeling, or model evaluation, and can work independently to produce precise, well-sourced questions and answers.

Salary Insight

Compensation is $30 to $60 per hour, paid per task that meets project specifications. Time per task varies with experience and workflow. Minimum submission requirements apply, and experts must submit a minimum number of tasks per week.

Pay and demand for Market Research & Insights roles

Aggregated

Typical pay

$70/hour

This role

$30–$60/hr

Most Market Research & Insights roles pay $40–$95 per hour. This role's pay falls inside that range.

Based on 1,065 similar roles that publish pay · 302 publish only a top rate; those count at the rate they gave

Typical rangeMedian payThis role

Rates shown per hour. Yearly and monthly pay converted; one-time fees and non-USD pay are not included.

Live similar roles
1,214
Listed in last 30 days
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Most requested skills · share of roles

  • ai training
    13%
  • ai evaluation
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  • llm evaluation
    11%
  • data annotation
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Figures from Market Research & Insights roles live on NearSkill when this page loaded. A role can close before you apply, so check the listing itself.

Compare your resume against these roles

Location

TypeRemote
LocationRemote
This is a remote position

Compensation

$30–60/hr

Required Skills

Research & source triangulationAttention to detailWritten precisionSelf-direction & reliabilityAnalytical thinkingResearch mastery

Application Tip

Highlight your research publications and any prior AI training, data labeling, or model evaluation work. Provide concrete examples of complex questions you have designed and sourced, showing how you verified answers with primary references.

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