About the Role
We're looking for experienced forestry and land management scientists to help shape how AI understands sustainable forestry, forest ecosystems, and land-use practices. Your field expertise will directly influence how next-generation AI systems reason about environmental decision-making — making a real-world impact from wherever you work.
- 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 and quality of AI-generated content related to forest health, land use, and sustainability
- Identify errors, oversimplifications, or misleading recommendations in AI outputs
- Provide clear, structured feedback to improve applied environmental reasoning in 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 land-use planning
- Able to critically evaluate applied environmental and management decision-making
- Comfortable reviewing and assessing written technical content
- Detail-oriented, self-motivated, and reliable
Nice to Have
- Degree in Forestry, Natural Resources, Environmental Science, or a related discipline
- Experience with conservation programs, land-use planning, or regulatory frameworks
- Familiarity with AI content evaluation or data annotation 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 understands the natural world
- Potential for ongoing work and contract extension