Remote Conservation Scientist: AI Training for Ecosystems

Alignerr Corp.; Melbourne; Remote; AUD 83,000 - 124,000; Full time

Job summary

Alignerr (Powered by Labelbox) seeks conservation professionals to help evaluate and improve AI systems trained on environmental science, land management, and conservation decision-making. Your expertise will shape how AI understands ecosystems, interprets data, and recommends land management strategies—making a real-world environmental impact.

You will review datasets, assess AI content for accuracy against real-world practices, and provide clear, actionable feedback.

Qualifications

• 3+ years in natural resource conservation, land management, or environmental science.
• Strong knowledge of ecosystems and conservation principles.
• Ability to evaluate scientific reasoning and identify gaps in applied recommendations.
• Comfortable reviewing structured written content and delivering detailed feedback.

Responsibilities

• Review conservation science questions, scenarios, and datasets used in AI training.
• Evaluate the scientific accuracy of AI-generated content related to land use, ecosystems, soil health, water systems, and biodiversity.
• Assess whether AI-generated recommendations reflect real-world conservation practices and standards.
• Provide clear, structured feedback to improve scientific reasoning and AI outputs.
• Work independently and asynchronously — on your own schedule, from anywhere.

Job description

Alignerr (Powered by Labelbox) seeks conservation professionals to help evaluate and improve AI systems trained on environmental science, land management, and conservation decision-making. Your expertise will shape how AI understands ecosystems, interprets data, and recommends land management strategies—making a real-world environmental impact.

You will review datasets, assess AI content for accuracy against real-world practices, and provide clear, actionable feedback.