Alignerr is looking for Wildlife and Habitat Conservation Scientist in Seattle, WA. This local job opportunity with ID 3662823831 is live since 2026-05-04 14:28:34. Wildlife and Habitat Conservation Scientist (AI Training) About the Role Are you a wildlife biologist or conservation scientist who wants to make an impact beyond the field? We're looking for conservation experts to help evaluate and improve AI systems trained on biodiversity protection and ecosystem management. Your scientific knowledge will directly shape how AI understands and communicates wildlife conservation - ensuring these systems reflect real-world ecological accuracy and sound conservation practice.
Organization : Alignerr (Powered by Labelbox)
Type : Hourly / Task-based Contract
Location : Remote
Commitment : 10-40 hours/week
What You'll Do
Review AI-generated wildlife and habitat conservation scenarios for scientific accuracy
Assess the quality of ecological reasoning and conservation strategies presented in AI outputs
Identify unrealistic assumptions, flawed methodology, or misapplied conservation approaches
Provide clear, structured feedback to improve the ecological validity of AI content
Work independently and asynchronously on your own schedule
Who You Are
3+ years of experience in wildlife biology, ecology, or habitat conservation
Strong working knowledge of biodiversity principles and ecosystem management
Able to critically evaluate applied ecological reasoning in written form
Comfortable reviewing and annotating structured scientific content
Self-motivated and reliable when working independently
Nice to Have
Graduate degree in Ecology, Wildlife Biology, or a related field
Hands-on field research or conservation program experience
Familiarity with AI tools or content evaluation workflows
Why Join Us
Work on cutting-edge AI projects at the intersection of science and technology
Fully remote and flexible - work on your own schedule from anywhere
Contribute to meaningful work that improves how AI handles critical environmental topics
Freelance perks: autonomy, variety, and global collaboration
Exposure to advanced large language models (LLMs) and how they're trained