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 evaluate and improve AI systems trained on sustainable forestry and land-use practices. Your field expertise will directly shape how AI understands forest ecosystems, management strategies, and environmental decision-making — making a real impact on how these critical topics are represented in next-generation AI tools. - 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 of AI-generated content related to forest health, land use, and sustainability practices - Identify factual errors, oversimplifications, or flawed reasoning in management recommendations - Provide clear, structured feedback to improve the quality of AI-generated applied reasoning - Work independently and asynchronously on your own schedule Who You Are - 3+ years of hands-on experience in forestry, land management, or a related field - Strong understanding of forest ecosystems, silviculture, and land management principles - Able to critically evaluate applied environmental and resource management decision-making - Comfortable reviewing and assessing written technical content with precision - Self-motivated, reliable, and able to meet deadlines without close supervision - No prior AI experience required Nice to Have - Degree in Forestry, Natural Resources, Environmental Science, or a related discipline - Experience with land-use planning, conservation programs, or regulatory compliance - Familiarity with AI systems or content evaluation workflows Why Join Us - Work on cutting-edge AI projects with top research labs shaping the future of AI - Fully remote and flexible — work on your own schedule, from anywhere - Freelance perks: autonomy, variety, and meaningful work with real-world impact - Contribute to ensuring AI gets environmental science right — for researchers, practitioners, and policymakers who rely on it - Potential for ongoing work and contract extension
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