About The Role We're looking for experienced forestry and land management scientists to help evaluate and improve AI systems trained on sustainable forestry and land-use practices. Your field expertise will directly shape how AI understands forest ecosystems, management decisions, and conservation strategies — making a real impact on how this technology serves the environmental science community.
Organization: Alignerr (Powered by Labelbox)
Type: Hourly / Task-based Contract
Location: Remote
Commitment: 10–40 hours/week
What You'll Do
Review forestry and land management scenarios used in AI training datasets
Assess the accuracy of AI-generated content related to forest health, land use, and sustainability practices
Identify factual errors, oversimplifications, or flawed management recommendations in AI outputs
Provide clear, structured feedback to improve the applied reasoning of AI systems
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, silviculture, and sustainable land-use practices
Ability to critically evaluate applied environmental decision-making scenarios
Comfortable reviewing and assessing written technical content
Detail-oriented, reliable, and self-motivated
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
Fully remote and flexible — work on your own schedule
Freelance perks: autonomy, variety, and global collaboration
Contribute to meaningful work that improves how AI handles real-world environmental science
Potential for ongoing work and contract extension
Skills
Human ResourcesTechnology, Information and Internet