Overview
micro1 engages Domain Contributor - Evaluation Specialists to support an internal project evaluating and improving advanced AI models. You'll apply your expertise to help train next-generation AI systems by designing domain-specific tasks, authoring evaluation questions, and assessing AI-generated outputs against authoritative sources.
What You’ll Do
- Design nuanced, domain-specific tasks that probe AI model limits and surface reasoning flaws
- Author questions and scenarios demanding deep subject knowledge, beyond general understanding
- Assess AI-generated outputs, validating accuracy against authoritative, primary sources in your area of expertise
- Document clear rationales for model shortcomings, specifying missed reasoning, source errors, or nuances
- Apply detailed task guidelines and evaluation rubrics consistently to each submission
- Submit completed deliverables independently on a rolling basis, meeting project requirements for written and verbal clarity
Requirements
- Domain depth in history, law, finance, journalism, or technology
- Source verification and research skills
- Reasoning clarity and evaluation expertise
- Proven hands-on experience with AI model training, annotation, RLHF, or evaluation
- Advanced research skills with track record of verifying complex claims against authoritative sources
- Exceptional written and verbal communication skills
- Demonstrated ability to precisely follow detailed instructions and evaluation frameworks
Who Should Apply
This role suits subject-matter experts (researchers, academics, compliance professionals, lawyers, financial analysts) who have hands-on experience evaluating or training AI systems and relish finding edge cases and reasoning flaws. It will frustrate generalists or people who lack deep domain expertise—the work demands authoritative knowledge in a specific field, not broad research skills alone. It also requires comfort working asynchronously and independently, submitting work to meet output targets rather than logging hours.
Salary Insight
The range $30–$60/hr is wide and output-based rather than hourly; your effective rate depends on how quickly you can design and evaluate tasks to the specification. At the lower end, this reflects recent graduates or emerging specialists; at the upper end, it signals experienced researchers or those with rare domain expertise. No minimum weekly hours are stated, only a minimum number of tasks, so clarify task scope and your throughput during onboarding to understand your realistic weekly earnings.
About Micro1
Platform connecting domain experts with AI training and evaluation projects, paid on a flexible contract basis.
Remote policy: Remote worldwide, excluding Afghanistan, Belarus, China, Cuba, Democratic Republic of the Congo, Hong Kong, Iran, Iraq, Libya, Macao, Myanmar, North Korea, Russia, Somalia, South Sudan, Sudan, Syria, Venezuela, Ukraine and Yemen. Individual projects may have…
How hiring works at Micro1 →Required Skills
Compensation
$30 - $60/hr
- Location
- Remote
- Engagement
- Contract
- Posted
- Oct 20
Opens micro1’s listing on MyRemoteJobs — we don’t collect applications ourselves.
About Micro1
Platform connecting domain experts with AI training and evaluation projects, paid on a flexible contract basis.
Remote policy: Remote worldwide, excluding Afghanistan, Belarus, China, Cuba, Democratic Republic of the Congo, Hong Kong, Iran, Iraq, Libya, Macao, Myanmar, North Korea, Russia, Somalia, South Sudan, Sudan, Syria, Venezuela, Ukraine and Yemen. Individual projects may have…
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Application Tip
Lead with a specific domain where you have both deep expertise and prior AI evaluation or annotation experience—state the project, the framework you used, and a concrete example of a flaw you surfaced in model reasoning. Hiring managers will prioritize applicants who can hit the ground running with both subject knowledge and familiarity with evaluation rubrics. If you lack formal AI experience, emphasize your track record of rigorous source verification and adversarial thinking in your field (e.g., identifying gaps in legal precedent, auditing financial claims, or catching historical inaccuracies).
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