Forestry and Land Management Scientist

About the Role

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

This is a fully remote, flexible contract role — work on your own schedule while making a meaningful contribution to cutting-edge AI development.

• 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, ecosystem management, land use, and sustainability practices
• Identify errors, oversimplifications, or flawed reasoning in AI-generated management recommendations
• Provide clear, structured feedback that helps improve how AI reasons through applied environmental decisions
• Work independently and asynchronously — no meetings, no set hours, just meaningful task-based work

Who You Are

• 3+ years of hands-on experience in forestry, land management, or a closely related field
• Strong working knowledge of forest ecosystems, sustainable land use, and resource management practices
• Able to critically evaluate applied environmental decision-making and spot where AI reasoning falls short
• Comfortable reading and reviewing written technical content with attention to detail
• Self-motivated and reliable when working independently on remote, asynchronous tasks

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, content evaluation workflows, or technical writing

Why Join Us

• Work on cutting-edge AI — contribute to some of the most advanced language model training projects in the field
• Fully remote and flexible — set your own hours and work from anywhere
• Autonomy and variety — no two tasks are the same; apply your expertise across diverse real-world scenarios
• Make a real impact — your domain knowledge directly improves how AI handles environmental science
• Global collaboration — work alongside a diverse network of subject matter experts from around the world
• Potential for ongoing work — strong contributors are considered for contract extensions and new projects