About the Role
We're looking for experienced forestry and land management scientists to help shape how AI understands sustainable forestry, land-use practices, and environmental decision-making. Your real-world expertise will directly influence the accuracy and reliability of AI systems being built for the future.
This is a fully remote, flexible contract role — work on your own schedule while contributing to cutting-edge AI research.
- Organization: Alignerr (Powered by Labelbox)
- Type: Hourly 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
- Identify errors, oversimplifications, or misleading recommendations in management guidance
- Provide clear, structured feedback to improve 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 foundational knowledge of forest ecosystems, silviculture, and sustainable land-use practices
- Able to critically evaluate applied environmental decision-making and management scenarios
- Comfortable reviewing and responding to written technical content with precision
- Self-motivated and reliable when working independently in a remote setting
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, content evaluation workflows, or data annotation platforms
Why Join Us
- Work on cutting-edge AI projects with top research labs and technology teams
- Fully remote and flexible — complete tasks on a schedule that works for you
- Freelance perks: autonomy, variety, and collaboration with a global network of experts
- Contribute to meaningful work that ensures AI gets environmental science right
- Potential for ongoing work and contract extension as projects grow