Data & Analytics

Agriculture, Forestry & Environmental Experts

micro1

Verified listing

Contract

RemotePosted Oct 14$40 - $60/hour

Overview

micro1 is a data lab that helps AI labs and enterprises train foundational models by producing high-quality training data. This role engages domain experts to contribute specialized knowledge in agriculture, forestry, and environmental science to advance AI systems that learn to reason and perform in real-world agricultural and environmental contexts.

What You’ll Do

Contribute domain-specific knowledge to support training and evaluation of AI-driven solutions in agriculture, forestry, and environmental science
Provide detailed assessments on industry practices, challenges, and innovations across agricultural engineering, food science, conservation, and land management
Review, annotate, and validate datasets, documents, and scenarios to ensure accuracy and relevance of AI systems in real-world applications
Create and refine technical content, process explanations, and policy guidance for diverse agricultural and environmental contexts
Advise on regulatory frameworks, sustainability initiatives, and emerging trends relevant to agriculture, forestry, and environmental conservation
Participate in written and verbal discussions to clarify project objectives, share insights, and align on deliverables
Support interdisciplinary collaboration among project stakeholders

Requirements

Minimum 5 years professional experience in agriculture, forestry, environmental conservation, or related subdomains
Proven expertise in sustainable agriculture, land management, or conservation practices
Strong written and verbal communication skills with emphasis on clarity and technical accuracy
Demonstrated ability to analyze complex systems, solve problems, and provide actionable recommendations
Familiarity with current regulatory standards, industry trends, and technological advancements in agriculture and environmental management
Experience collaborating on interdisciplinary projects or with cross-functional teams

Who Should Apply

This role suits seasoned agriculture, forestry, or conservation professionals who think clearly in writing, enjoy explaining technical concepts to non-experts, and want flexible contract work without committing to a full-time position. It will frustrate you if you're an implementer who needs concrete deliverables and closure; the work here is abstract (training AI systems) and open-ended, and you won't see immediate real-world outcomes from your annotations.

Salary Insight

The $40–60/hour range reflects contractor pay (typically higher hourly than equivalent salaries) for specialized domain expertise. This is positioned as a data-production role where your primary value is subject-matter authority rather than technical AI skills, so compensation scales with depth of real-world experience. Clarify upfront whether hours are capped or flexible, and whether the rate accounts for unpaid preparation time if annotation requires research.

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

Agricultural EngineeringEnvironmental ConservationSustainable AgricultureLand ManagementAI Training Data

Compensation

$40 - $60/hour

Location: Remote
Engagement: Contract
Posted: Oct 14

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.

How hiring works at Micro1 →

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Application Tip

Lead with a specific, complex system or challenge you've personally managed—not a job title or a list of credentials. For example: "I spent three years designing rotational grazing protocols for mixed-species operations across variable soil types, and I can articulate both the decision-making framework and the edge cases where standard practice breaks down." This signals you can generate the nuanced, multi-perspective training data micro1 actually needs. The hiring team wants to know whether you can explain your domain with the precision required to teach an AI system.

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