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Forestry and Land Management Scientist (AI Training)

$30-55/hrRemoteFreelanceSTEM

About the Role

We're looking for experienced forestry and land management professionals to help shape how AI understands sustainable land use, forest ecosystems, and environmental decision-making. Your field expertise will directly influence the accuracy and reliability of next-generation AI systems — making a real-world impact from wherever you work.

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

What You'll Do

  • Review and evaluate AI-generated forestry and land management scenarios for scientific accuracy
  • Assess content related to forest health, land use planning, and sustainability practices
  • Identify errors, oversimplifications, or flawed reasoning in AI-generated management recommendations
  • Provide clear, structured feedback that improves how AI models reason about applied environmental challenges
  • Work independently and asynchronously on your own schedule

Who You Are

  • 3+ years of hands-on experience in forestry, land management, or a closely related field
  • Strong working knowledge of forest ecosystems, land-use practices, and sustainability principles
  • Able to critically evaluate applied environmental decision-making and management strategies
  • Comfortable reading and reviewing detailed technical written content
  • Self-motivated and reliable when working independently

Nice to Have

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

Why Join Us

  • Work on cutting-edge AI projects with top research labs and help shape how AI understands the natural world
  • Fully remote and flexible — work on your own schedule, from anywhere
  • Freelance perks: autonomy, variety, and global collaboration
  • Contribute to meaningful work at the intersection of environmental science and artificial intelligence
  • Potential for ongoing work and contract extension