AI Training: Remote Wildlife Conservation Scientist

Alignerr Corp.; Manchester; Remote; GBP 55,000 - 83,000; Part time

Benefits offered by this job

Autonomy

Flexible schedule

Global expert community

Job summary

Alignerr Corp. invites wildlife biology and ecology professionals to help evaluate AI outputs used in biodiversity protection and ecosystem management. This remote, hourly contract role offers flexible scheduling and a chance to influence conservation science in real projects.

You will review AI-generated scenarios, assess ecological reasoning, and provide structured feedback to improve accuracy and applicability. Prior experience and a graduate degree are preferred for ongoing collaboration.

Qualifications

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

Responsibilities

• Review AI-generated wildlife and habitat conservation scenarios for scientific accuracy
• Assess the quality of ecological reasoning and proposed conservation strategies
• Identify unrealistic assumptions, flawed methodologies, or misapplied conservation principles
• Provide clear, structured feedback to improve the ecological validity of AI outputs
• Work independently and asynchronously on your own schedule

Skills

Wildlife biology

Ecology

Critical evaluation

Education

Graduate degree in Ecology or related field

Tools

AI review workflows

Job description

Alignerr Corp. invites wildlife biology and ecology professionals to help evaluate AI outputs used in biodiversity protection and ecosystem management. This remote, hourly contract role offers flexible scheduling and a chance to influence conservation science in real projects.

You will review AI-generated scenarios, assess ecological reasoning, and provide structured feedback to improve accuracy and applicability. Prior experience and a graduate degree are preferred for ongoing collaboration.