About The Role
We're looking for experienced forestry and land management scientists to help shape how AI understands sustainable forestry, forest ecosystems, and land-use practices. Your domain expertise will directly influence the accuracy and reliability of AI systems used by researchers, practitioners, and decision-makers worldwide.
This is a fully remote, flexible contract role — work on your own schedule while contributing to cutting-edge AI development.
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Organization: Alignerr (Powered by Labelbox)
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Type: Hourly / Task-based Contract
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Location: Remote
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Commitment: 10–40 hours/week
What You'll Do
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Review and evaluate forestry and land management scenarios used in AI training datasets
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Assess the accuracy and soundness of AI-generated content related to forest health, land use, and sustainability
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Identify factual errors, oversimplifications, or flawed management recommendations
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Provide clear, structured feedback to improve AI reasoning on applied environmental topics
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Work independently and asynchronously to complete task-based assignments on your own schedule
Who You Are
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3+ years of hands-on experience in forestry, land management, or a closely related field
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Strong working knowledge of forest ecosystems, silviculture, and sustainable land management practices
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Able to critically evaluate applied environmental decision-making scenarios
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Comfortable reading and reviewing technical written content with precision
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Self-motivated and reliable — you deliver quality work without close supervision
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No prior AI experience required
Nice to Have
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Degree in Forestry, Natural Resources, Environmental Science, or a related discipline
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Experience with land-use planning, conservation programs, or regulatory frameworks
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Familiarity with AI systems, content evaluation, or data annotation workflows
Why Join Us
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Work on cutting-edge AI projects with top research labs
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Fully remote and flexible — work when and where it suits you
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Freelance perks: autonomy, variety, and global collaboration
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Make a meaningful impact by ensuring AI gets environmental science right
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Potential for ongoing work and contract extension