Forestry And Land Management Scientist AI Training

About The Role

We're looking for experienced forestry and land management scientists to help shape how AI understands sustainable forestry, forest health, and land-use decision-making. Your real-world expertise will directly influence the accuracy and reliability of AI systems used by researchers, policymakers, and conservation professionals worldwide.

This is a fully remote, flexible contract role — work on your own schedule while making a meaningful contribution to the future of AI in environmental science.

• Organization: Alignerr (Powered by Labelbox)
• Type: Hourly / Task-based Contract
• Location: Remote
• Commitment: 10–40 hours/week
  
  

• Review AI-generated forestry and land management scenarios for scientific accuracy and practical soundness
• Evaluate content related to forest health, biodiversity, land use, and sustainability practices
• Identify errors, oversimplifications, or misleading recommendations in AI outputs
• Assess the quality of applied environmental decision-making presented by AI systems
• Provide clear, structured feedback that helps improve AI reasoning and reliability
• Work independently and asynchronously — no meetings required
  
  

• 3+ years of hands-on experience in forestry, land management, or a closely related field
• Strong working knowledge of forest ecosystems, management techniques, and sustainability principles
• Able to critically evaluate applied environmental recommendations and flag inaccuracies
• Comfortable reviewing and providing feedback on written technical content
• Self-motivated, detail-oriented, and reliable
  
  

• Degree in Forestry, Natural Resources, Environmental Science, or a related discipline
• Experience with land-use planning, conservation programs, or regulatory compliance
• Familiarity with AI systems or content evaluation workflows
  
  

• Work on cutting-edge AI projects with real-world environmental impact
• Fully remote and flexible — work when and where it suits you
• Freelance perks: autonomy, variety, and global collaboration
• Gain exposure to advanced AI systems and how large language models are trained
• Potential for ongoing work and contract extension