Environmental Management Scientist (AI Training)
About this role
About the Role We're looking for 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 used by researchers, policymakers, and practitioners worldwide. This is a fully remote, flexible contract role where your knowledge genuinely matters — you're not just reviewing content, you're helping AI get environmental science right. - Organization: Alignerr (Powered by Labelbox) - Type: Hourly / Task-based 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 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 related field - Strong working knowledge of sustainability frameworks, environmental planning, and impact assessment - Able to critically evaluate written environmental analyses with a practiced eye - Skilled at delivering detailed, structured, and constructive feedback - Self-motivated and comfortable managing your own workload remotely 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 systems, content evaluation, or data annotation workflows Why Join Us - Work on cutting-edge AI projects with top research labs - Fully remote and flexible — work on your own schedule, anywhere - Freelance perks: autonomy, variety, and global collaboration - Contribute to meaningful work that improves how AI handles real environmental challenges - Exposure to advanced large language models (LLMs) and how they're trained - Potential for ongoing work and contract extension
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