Natural Resource Conservation Scientist

Alignerr Corp.; France; Remote; EUR 14,000 - 55,000; Full time

Benefits offered by this job

Fully remote

Flexible schedule

Hourly/Task-based contract

Job summary

Alignerr is seeking a Natural Resource Conservation Scientist to help shape how AI understands the natural world. This fully remote, hourly contract role invites experts to review and improve AI training content on conservation topics, ensuring science-based accuracy.

You will work independently on 10–40 hours per week, evaluate AI-generated content across ecosystems, land and water management, and provide detailed feedback to strengthen AI rigor.

Qualifications

• 3+ years of professional experience in natural resource conservation, land management, or environmental science.
• Strong foundational knowledge of ecosystems, conservation principles, and applied land and water management.
• Ability to critically evaluate AI-generated scientific reasoning against professional standards.
• Experience providing detailed, constructive feedback on structured content.

Responsibilities

• 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 health, water systems, and biodiversity.
• Assess whether AI recommendations reflect sound, real-world conservation practices.
• Identify gaps, errors, or misleading reasoning in AI outputs and provide structured, actionable feedback.
• Help improve the scientific rigor and quality of AI-generated environmental content.
• Work independently and asynchronously to complete task-based assignments.

Skills

Conservation experience

Ecosystems knowledge

Analytical evaluation

Scientific writing

Self-motivated

Education

MS/PhD in natural resources

Job description

Natural Resource Conservation Scientist (AI Training)

What if your expertise in ecosystems, land management, and conservation could help shape how AI understands the natural world? We're looking for experienced natural resource conservation scientists to evaluate and improve AI systems trained on environmental science content — ensuring that the next generation of AI gets conservation right.

This is a fully remote, flexible contract role that lets you contribute to cutting-edge AI research on your own schedule.

• Organization: Alignerr (Powered by Labelbox)
• Type: Hourly / Task-based Contract
• 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 health, water systems, and biodiversity
• Assess whether AI recommendations reflect sound, real-world conservation practices
• Identify gaps, errors, or misleading reasoning in AI outputs and provide structured, actionable feedback
• Help improve the scientific rigor and quality of AI-generated environmental content
• Work independently and asynchronously to complete task-based assignments

Who You Are

• 3+ years of professional experience in natural resource conservation, land management, or environmental science
• Strong foundational knowledge of ecosystems, conservation principles, and applied land and water management
• Able to critically evaluate scientific reasoning and identify where AI outputs fall short of professional standards
• Comfortable working with structured written content and providing detailed, constructive feedback
• Self-motivated, reliable, and able to meet deadlines without close supervision

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

• Make a real impact — your scientific expertise directly shapes how AI reasons about conservation and the environment
• Fully remote and flexible — work from anywhere, on a schedule that suits you
• Cutting-edge AI work — gain exposure to advanced large language models (LLMs) and how they're trained and evaluated
• Autonomy and variety — task-based work across a range of environmental science topics
• Global collaboration — work alongside a diverse network of subject matter experts
• Potential for ongoing work — strong contributors are considered for contract extensions and expanded projects