Natural Resource Conservation Scientist

Alignerr Corp.; Boston (MA); À distance; USD 55 000 - 96 000; Temps partiel

Avantages offerts par ce poste

Remote work

Flexible hours

Contract work

Résumé du poste

Alignerr Corp. is seeking experienced natural resource conservation scientists to shape AI training. You will review conservation questions and assess AI content for accuracy across ecosystems and land management topics.

The role is remote and flexible, offering hourly, task-based work with 10–40 hours per week. Candidates should bring 3+ years in conservation or environmental science and a strong foundation in ecological principles.

Qualifications

• 3+ years of professional experience in natural resource conservation or environmental science.
• Strong foundational knowledge of ecosystems and land management strategies.
• Able to critically evaluate scientific reasoning and provide clear feedback.
• Comfortable reviewing structured written content and delivering actionable feedback.
• Nice-to-have: Master's/PhD in Natural Resources, Environmental Science, Ecology, or related discipline.

Responsabilités

• Review conservation science questions and real-world scenarios used to train AI models.
• Evaluate the scientific accuracy of AI-generated content covering land use, ecosystems, soil health, water systems, and biodiversity.
• Assess whether AI outputs reflect sound, real-world conservation practices and land management principles.
• Provide clear, structured feedback to improve the scientific reasoning behind AI responses.
• Work independently and asynchronously — on your schedule, at your pace.

Connaissances

Ecosystem knowledge

Conservation principles

Scientific reasoning

Written feedback

Formation

Master's degree or PhD in Natural Resources or related

Description du poste

Natural Resource Conservation Scientist (AI Training)

We're looking for experienced natural resource conservation scientists to help shape the next generation of AI. Your field expertise will directly influence how AI systems understand ecosystems, land management, biodiversity, and conservation decision-making — work that matters far beyond any single project.

This is a fully remote, flexible contract role built for working professionals who want to contribute their scientific knowledge to cutting-edge AI development on their own schedule.

• Organization: Alignerr (Powered by Labelbox)
• Type: Hourly / Task-Based Contract
• Location: Remote
• Commitment: 10–40 hours/week

What You'll Do

• Review conservation science questions and real-world scenarios used to train AI models
• Evaluate the scientific accuracy of AI-generated content covering land use, ecosystems, soil health, water systems, and biodiversity
• Assess whether AI outputs reflect sound, real-world conservation practices and land management principles
• Provide clear, structured feedback to improve the scientific reasoning behind AI responses
• Work independently and asynchronously — on your schedule, at your pace

Who You Are

• 3+ years of professional experience in natural resource conservation, environmental science, or a related field
• Strong foundational knowledge of ecosystems, land management strategies, and conservation principles
• Able to critically evaluate scientific reasoning and applied recommendations with clarity and precision
• Comfortable reviewing structured written content and delivering detailed, actionable feedback
• Self-motivated and reliable in a remote, asynchronous work environment

Nice to Have

• Master's degree or PhD in Natural Resources, Environmental Science, Ecology, or a related discipline
• Hands-on fieldwork or applied conservation experience
• Familiarity with AI systems, content evaluation workflows, or scientific writing

Why Join Us

• Meaningful impact — your expertise helps ensure AI handles environmental science responsibly and accurately
• Work on cutting-edge AI — gain exposure to advanced large language models (LLMs) and how they're trained
• Fully remote and flexible — work when and where it suits you, with no fixed hours
• Freelance autonomy — task-based structure gives you control over your workload
• Global collaboration — join a diverse network of subject matter experts contributing to AI development worldwide
• Potential for ongoing work — strong contributors are considered for contract extensions and future projects