Forestry and Land Management Scientist (AI Training)

About The Role We're looking for experienced forestry and land management scientists to help shape how AI understands sustainable forestry, land-use practices, and environmental decision-making. Your real-world expertise will directly influence the accuracy and reliability of AI systems being built for the future. This is a fully remote, flexible contract role — work on your own schedule while contributing to cutting-edge AI research. Organization: Alignerr (Powered by Labelbox) Type: Hourly 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 Identify errors, oversimplifications, or misleading recommendations in management guidance Provide clear, structured feedback to improve AI reasoning on applied environmental topics 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 foundational knowledge of forest ecosystems, silviculture, and sustainable land-use practices Able to critically evaluate applied environmental decision-making and management scenarios Comfortable reviewing and responding to written technical content with precision Self-motivated and reliable when working independently in a remote setting Nice to Have Degree in Forestry, Natural Resources, Environmental Science, or a related discipline Experience with land-use planning, conservation programs, or regulatory frameworks Familiarity with AI tools, content evaluation workflows, or data annotation platforms Why Join Us Work on cutting-edge AI projects with top research labs and technology teams Fully remote and flexible — complete tasks on a schedule that works for you Freelance perks: autonomy, variety, and collaboration with a global network of experts Contribute to meaningful work that ensures AI gets environmental science right Potential for ongoing work and contract extension as projects grow