Natural Resource Conservation Scientist

Alignerr; Dallas (TX); Remote; USD 55,000 - 96,000; Part time

Benefits offered by this job

Autonomy

Variety of projects

Global collaboration

Job summary

Alignerr, operating with Labelbox, seeks experienced natural resource conservation scientists for AI training assessment. You will review conservation science questions and scenarios in AI datasets, ensure accuracy across ecosystems, land use, soil, water, and biodiversity, and provide structured feedback.

Remote, freelance hours welcomed. Ideal candidates have 3+ years in environmental science and can work independently on task-based projects with flexible scheduling.

Qualifications

• 3+ years of professional experience in natural resource conservation or environmental science.
• Strong working knowledge of ecosystems, land management principles, and conservation frameworks.
• Ability to critically evaluate scientific reasoning and applied recommendations.
• Comfortable reviewing structured written content and providing clear, detailed feedback.

Responsibilities

• Review conservation science questions and 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 recommendations reflect real-world conservation practices and sound scientific reasoning.
• Identify gaps, errors, or misleading outputs and provide structured, detailed feedback.

Skills

Natural resource conservation

Ecosystems knowledge

Critical evaluation

Written feedback

Education

Master's degree in Natural Resources / Environmental Science

PhD in Natural Resources / Environmental Science

Tools

AI systems familiarity

Job description

Natural Resource Conservation Scientist (AI Training)

AI is rapidly expanding into environmental science — and it needs experts like you to get it right. We're looking for experienced natural resource conservation scientists to help evaluate and improve AI systems trained on conservation science, land management, and environmental decision-making.

Your real-world expertise will directly shape how AI understands ecosystems, interprets land use data, and recommends conservation strategies — making a meaningful impact on how this technology serves the planet.

• 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 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 recommendations reflect real-world conservation practices and sound scientific reasoning
• Identify gaps, errors, or misleading outputs and provide structured, detailed feedback
• Work independently and asynchronously on your own schedule

Who You Are

• 3+ years of professional experience in natural resource conservation or environmental science
• Strong working knowledge of ecosystems, land management principles, and conservation frameworks
• Able to critically evaluate scientific reasoning and applied recommendations
• Comfortable reviewing structured written content and providing clear, detailed feedback
• Self-motivated and reliable when working independently on task-based projects

Nice to Have

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

Why Join Us

• Work on cutting‑edge AI projects that intersect environmental science and emerging technology
• Fully remote and flexible — work on your own schedule, from anywhere
• Freelance perks: autonomy, variety, and collaboration with a global network of experts
• Contribute to work that helps AI handle environmental topics more accurately and responsibly
• Potential for ongoing work and contract extension