Natural Resource Conservation Scientist

Natural Resource Conservation Scientist (AI Training)

About The Role
Your expertise in natural resource conservation could help shape how AI understands the natural world. We're looking for experienced conservation and environmental science professionals to evaluate and improve AI systems trained on land management, ecosystem science, and conservation decision-making. This is a fully remote, flexible contract role — work on your own schedule while contributing to cutting-edge AI development that touches real-world environmental outcomes.
• Organization: Alignerr (Powered by Labelbox)
• Type: Hourly / Task-based Contract
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Location:
Remote
• Commitment: 10–40 hours/week

What You'll Do
• Review conservation science questions and real-world scenarios used in AI training datasets
• Evaluate the scientific accuracy of AI-generated content covering land use, ecosystems, soil, water, and biodiversity
• Assess whether AI-generated recommendations reflect sound, real-world conservation practices
• Provide clear, structured feedback to improve AI scientific reasoning and outputs
• Work independently and asynchronously to meet project milestones on your own schedule Who You Are
• 3+ years of professional experience in natural resource conservation, land management, or environmental science
• Strong working knowledge of ecosystems, conservation principles, and applied land management practices
• Able to critically evaluate scientific reasoning and identify gaps or inaccuracies in applied recommendations
• Comfortable reviewing structured written content and providing detailed, constructive feedback
• Self-motivated and reliable when working independently in a remote environment Nice to Have
• Master's degree or PhD in Natural Resources, Environmental Science, Ecology, or a related field
• Hands-on fieldwork or applied conservation project experience
• Familiarity with AI systems, content evaluation workflows, or data annotation platforms Why Join Us
• Work on cutting-edge AI projects with real environmental science impact
• Fully remote and flexible — design your own work schedule
• Freelance perks: autonomy, variety, and global collaboration
• Gain exposure to advanced large language models (LLMs) and how they're trained
• Potential for ongoing work and contract extension