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Alignerr

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 tackling some of the most important challenges of our time. This is a fully remote, flexible contract role — work on your own schedule and apply your knowledge in an exciting new frontier. - 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 environmental models and real-world practice - Provide clear, structured feedback to improve the accuracy and applicability of AI outputs - Work independently and asynchronously to complete task-based assignments 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 and environmental planning principles - Able to critically evaluate written environmental analyses for accuracy, completeness, and practical relevance - Comfortable providing detailed, structured written feedback - Self-motivated and reliable when working independently - No prior AI experience required Nice to Have - Master's degree in Environmental Management, Environmental Science, or a related discipline - Experience with environmental policy, regulatory frameworks, or compliance - Familiarity with AI systems or content evaluation workflows Why Join Us - Work on cutting-edge AI projects with top research labs - 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 addresses 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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