Remote AI Conservation Scientist — Environmental Data QA

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

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.