Environmental Management Scientist (AI Training)

About the Role: We're looking for experienced environmental management professionals to help evaluate and improve AI systems trained on sustainability, land-use planning, and environmental decision-making. Your real-world expertise will directly shape how AI understands and communicates complex environmental topics - making a tangible impact on how these tools serve practitioners, policymakers, and the planet. 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 environmental models and real-world practice Flag inaccuracies, oversimplifications, or misleading guidance in AI outputs Provide clear, structured feedback that improves the accuracy and applicability of AI content Work independently and asynchronously on task-based assignments that fit your 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 and identify where they fall short Comfortable providing detailed, well-organized written feedback Self-motivated, reliable, and comfortable working independently

Nice to Have: Master's degree in Environmental Management, Environmental Science, or a related discipline Experience with environmental policy, regulatory compliance, or EIA frameworks Familiarity with AI tools or content evaluation workflows

Why Join Us: Work on cutting-edge AI projects with top research labs and make a real difference in how AI handles environmental topics Fully remote and flexible - work on your own schedule, wherever you are Freelance perks: autonomy, variety, and global collaboration Gain firsthand exposure to advanced large language models (LLMs) and how they're trained Potential for ongoing work and contract extension