Forestry and Land Management Scientist (AI Training)

About The Role

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

What You'll Do

• Review forestry and land management scenarios used in AI training datasets
• Assess the accuracy, depth, and scientific soundness of content related to forest health, land use, and sustainability
• Identify factual errors, oversimplifications, or flawed management recommendations
• Provide clear, structured feedback that improves AI reasoning on applied environmental topics
• Work independently and asynchronously to complete task-based assignments 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 and management scenarios
• Comfortable reviewing and responding to written technical content
• Self-motivated, reliable, and able to work independently without close supervision

Nice to Have

• Degree in Forestry, Natural Resources, Environmental Science, or a related discipline
• Experience with land-use planning, conservation programs, or environmental policy
• Familiarity with AI content evaluation, annotation, or data labeling workflows

Why Join Us

• Work on cutting-edge AI projects with top research labs
• Fully remote and flexible — work on your own schedule, anywhere
• Freelance perks: autonomy, variety, and global collaboration
• Contribute to meaningful work that improves how AI handles real environmental challenges
• Potential for ongoing work and contract extension