Remote Wildlife & Habitat Conservation Scientist for AI

Alignerr Corp.; Australia; Remote; AUD 55,000 - 96,000; Part time

Job summary

Alignerr (Powered by Labelbox) seeks a Wildlife and Habitat Conservation Scientist to influence AI training data for biodiversity and conservation science. This fully remote hourly contract offers 10–40 hours per week, flexible scheduling, and the chance to impact cutting-edge AI technology.

Applicants should have 3+ years of hands-on wildlife biology or ecology experience and a strong grasp of biodiversity principles to review and annotate ecological content for AI systems.

Qualifications

• 3+ years of hands-on experience in wildlife biology, ecology, or habitat conservation.
• Strong working knowledge of biodiversity principles and ecosystem management.
• Able to critically evaluate applied ecological reasoning presented in written scenarios.
• Comfortable reviewing and annotating structured scientific content.
• Detail-oriented, self-motivated, and reliable.

Responsibilities

• Review wildlife and habitat conservation scenarios used in AI training datasets.
• Evaluate the accuracy of ecological reasoning, species assessments, and conservation strategies.
• Identify unrealistic assumptions, flawed methodologies, or misapplied conservation practices.
• Provide clear, structured feedback to improve the scientific validity of AI outputs.
• Work independently and asynchronously to complete task-based assignments on your schedule.

Skills

Wildlife biology

Ecology

Data annotation

Education

Graduate degree in Ecology, Wildlife Biology, Conservation Science, or related field

Tools

AI annotation workflows

Job description

Alignerr (Powered by Labelbox) seeks a Wildlife and Habitat Conservation Scientist to influence AI training data for biodiversity and conservation science. This fully remote hourly contract offers 10–40 hours per week, flexible scheduling, and the chance to impact cutting-edge AI technology.

Applicants should have 3+ years of hands-on wildlife biology or ecology experience and a strong grasp of biodiversity principles to review and annotate ecological content for AI systems.