Forestry and Land Management Scientist (AI Training)
About this role
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 field 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. - Organization: Alignerr (Powered by Labelbox) - Type: Hourly / Task-Based Contract - Location: Remote - Commitment: 10–40 hours/week What You'll Do - Review forestry and land management scenarios used in AI training datasets - Assess the accuracy and depth of AI-generated content related to forest health, land use, and sustainability - Identify errors, oversimplifications, or misleading recommendations in management guidance - Provide structured, expert feedback to improve AI reasoning on applied environmental decisions - Work independently and asynchronously to complete task-based assignments on your own schedule Who You Are - 3+ years of hands-on experience in forestry, land management, or a closely related field - Strong working knowledge of forest ecosystems, silviculture, and sustainable land-use practices - Able to critically evaluate applied environmental decision-making and management recommendations - Comfortable reading and reviewing technical written content with precision and consistency - Self-motivated and reliable — able to work independently without close supervision Nice to Have - Degree in Forestry, Natural Resources, Environmental Science, or a related discipline - Experience with land-use planning, conservation programs, or environmental policy - Familiarity with AI systems, content evaluation, or annotation workflows Why Join Us - Work on cutting-edge AI projects alongside top research labs - Fully remote and flexible — structure your work around your life - Freelance perks: autonomy, variety, and global collaboration - Make a tangible impact on how AI handles real-world environmental challenges - Potential for ongoing work and contract extension
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