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