AI Training Conservation Scientist (Remote, Flexible)

Alignerr Corp.; 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

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.