02 oct
|
Alignerr
|
Ciudad de México
02 oct
Alignerr
Ciudad de México
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 adaptable — 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
📌 Forestry and Land Management Scientist (Ciudad de México)
🏢 Alignerr
📍 Ciudad de México