Natural Resource Conservation Scientist

Alignerr Corp.; Johannesburg; Remote; ZAR 248,000 - 441,000; Part time

Job summary

Alignerr, a remote-first research partner, seeks a Natural Resource Conservation Scientist for AI training. This hourly, task-based contract lets you work flexibly 10–40 hours/week from anywhere.

Bring 3+ years in conservation, strong ecosystem and land-management knowledge, and the ability to critique AI-generated content with precise, actionable feedback. Masters/PhD and field experience are a plus.

Qualifications

• 3+ years of professional experience in natural resource conservation or environmental science.
• Strong knowledge of ecosystems, land management, and conservation frameworks.
• Ability to assess scientific reasoning and provide precise, actionable feedback.
• Comfortable reviewing structured written content in a remote, asynchronous setting.

Responsibilities

• Review conservation science questions and case studies used in AI training datasets.
• Evaluate the scientific accuracy of AI-generated content on ecosystems, soil, water, and biodiversity.
• Assess alignment of AI recommendations with real-world conservation practices.
• Provide clear, structured feedback to improve AI outputs.
• Work independently and asynchronously on task-based assignments.

Skills

Ecosystem knowledge

Land management

Conservation frameworks

Scientific reasoning evaluation

Remote work discipline

Education

Master's degree or PhD in Natural Resources or related

Job description

Natural Resource Conservation Scientist (AI Training)

About The Role

What if your expertise in ecosystems, land management, and conservation could help shape how AI understands and communicates environmental science? We're looking for experienced natural resource conservation scientists to join a cutting-edge AI training project. Your scientific knowledge will directly influence how AI systems reason about conservation challenges — from biodiversity and soil health to water systems and land use decision-making. This is a fully remote, flexible contract role that fits around your 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, scenarios, and case studies 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 align with real-world conservation practices and standards
• Provide clear, structured feedback to improve the scientific reasoning and quality of AI outputs
• Work independently and asynchronously to complete task-based assignments on your own schedule

Who You Are

• 3+ years of professional experience in natural resource conservation, environmental science, or a closely related field
• Strong working knowledge of ecosystems, land management principles, and conservation frameworks
• Able to critically evaluate scientific reasoning and applied recommendations with precision
• Comfortable reviewing structured written content and delivering detailed, actionable feedback
• Self-motivated and reliable in a remote, independent 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 project experience
• Familiarity with AI systems, content evaluation, or data annotation workflows

Why Join Us

• Work on the frontier of AI — contribute to projects with top AI research labs and directly influence how AI handles complex environmental topics
• Fully remote and flexible — work from anywhere, on your own schedule, with no fixed hours
• Freelance autonomy — task-based work that respects your time and expertise
• Meaningful impact — your conservation knowledge helps ensure AI gives accurate, responsible guidance on real environmental issues
• Global collaboration — work alongside a diverse community of subject-matter experts from around the world
• Potential for ongoing work — high-performing contributors are considered for contract extensions and new projects