Role Overview:

As a Natural Resource Conservation Scientist at Alignerr (Powered by Labelbox), your main responsibility will be to evaluate and improve AI systems trained on environmental science, land management, and conservation decision-making. You will review conservation science questions and scenarios, evaluate scientific accuracy of content, assess AI-generated recommendations, provide structured feedback, and work independently to meet project deadlines.

Key Responsibilities:

• Review conservation science questions and scenarios used in AI training.
• Evaluate the scientific accuracy of content related to land use, ecosystems, soil, water, and biodiversity.
• Assess whether AI-generated recommendations reflect real-world conservation practices.
• Provide structured feedback to improve scientific reasoning and outputs.
• Work independently and asynchronously to meet project deadlines.

Qualifications Required:

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

Additional Details:

Alignerr (Powered by Labelbox) offers competitive pay, flexible remote work, the opportunity to lead a team working on cutting-edge AI projects, exposure to advanced LLMs and how they're trained, freelance perks such as autonomy, flexibility, and global collaboration, and the potential for contract extension.

To apply, you need to submit your resume, complete a short screening, and go through project matching and onboarding. Please note that the team reviews applications daily, so it is important to complete the necessary steps to be considered for this opportunity. Role Overview:

As a Natural Resource Conservation Scientist at Alignerr (Powered by Labelbox), your main responsibility will be to evaluate and improve AI systems trained on environmental science, land management, and conservation decision-making. You will review conservation science questions and scenarios, evaluate scientific accuracy of content, assess AI-generated recommendations, provide structured feedback, and work independently to meet project deadlines.

Key Responsibilities:

• Review conservation science questions and scenarios used in AI training.
• Evaluate the scientific accuracy of content related to land use, ecosystems, soil, water, and biodiversity.
• Assess whether AI-generated recommendations reflect real-world conservation practices.
• Provide structured feedback to improve scientific reasoning and outputs.
• Work independently and asynchronously to meet project deadlines.

Qualifications Required:

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

Additional Details:

Alignerr (Powered by Labelbox) offers competitive pay, flexible remote work, the opportunity to lead a team working on cutting-edge AI projects, exposure to advanced LLMs and how they're trained, freelance perks such as autonomy, flexibility, and global collaboration, and the potential for contract extension.

To apply, you need to submit your resume, complete a short screening, and go through project matching and onboarding. Please note that the team reviews applications daily, so it is important to complete the necessary steps to be considered for this opportunity.