Forestry and Land Management Scientist

Forestry and Land Management Scientist (AI Training)

About the Role

We're looking for experienced forestry and land management scientists to help shape the next generation of AI. Your field expertise will directly influence how AI systems understand, reason about, and communicate sustainable forestry and land-use practices — making a real-world impact on how this technology serves environmental professionals and decision-makers.

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

What You'll Do

• Review AI-generated forestry and land management scenarios for scientific accuracy and practical soundness
• Assess content related to forest health, land use planning, and sustainability best practices
• Identify factual errors, oversimplifications, or flawed management recommendations in AI outputs
• Provide clear, structured feedback to improve AI reasoning on applied environmental topics
• Work independently and asynchronously — on a schedule that fits your life

Who You Are

• 3+ years of hands-on experience in forestry, land management, or a closely related field
• Deep understanding of forest ecosystems, silviculture, and sustainable land-use practices
• Confident evaluating applied environmental decision-making and technical recommendations
• Comfortable reviewing and critiquing written scientific or professional content
• Self-directed and reliable — you can manage your own time and meet deadlines

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 tools or content evaluation workflows

Why Join Us

• Work on cutting-edge AI projects with top research labs
• Fully remote and flexible — set your own hours and work from anywhere
• Freelance perks: autonomy, variety, and collaboration with a global expert community
• Contribute to meaningful work that improves AI's understanding of our natural world
• Potential for ongoing work and contract extension