Environmental Management Scientist (AI Training)

About The Role We're looking for experienced environmental management professionals to help shape how AI understands sustainability, land-use planning, and environmental decision-making. Your real-world expertise will directly influence the quality and accuracy of AI systems being used across research, policy, and industry — work that genuinely matters. Organization: Alignerr (Powered by Labelbox) Type: Hourly Contract Location: Remote Commitment: 10–40 hours/week What You'll Do Review and evaluate AI-generated environmental management scenarios, analyses, and recommendations Assess the quality of AI reasoning related to sustainability frameworks, impact mitigation, and resource planning Identify gaps between theoretical approaches and real-world environmental practice Provide clear, structured feedback to improve the accuracy, depth, and applicability of AI outputs Work independently and asynchronously on your own schedule Who You Are 3+ years of hands-on experience in environmental management, conservation, or a closely related field Strong working knowledge of sustainability frameworks, environmental planning, and impact assessment Able to critically evaluate written environmental analyses and identify practical shortcomings Comfortable delivering detailed, structured written feedback Self-motivated and reliable when working independently on task-based assignments Nice to Have Master's degree in Environmental Management, Environmental Science, or a related discipline Experience with environmental policy, regulatory compliance, or permitting frameworks Familiarity with AI tools or content evaluation workflows Why Join Us Work on cutting-edge AI projects with top research labs and help define how AI handles complex environmental topics Fully remote and flexible — work on your own schedule, from anywhere Freelance perks: autonomy, variety, and global collaboration Contribute to meaningful work that improves how AI supports sustainability and environmental decision-making Potential for ongoing work and contract extension