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