Remote Wildlife AI Quality Reviewer

Alignerr Corp.; Chicago (IL); Remote; USD 34,000 - 55,000; Part time

Benefits offered by this job

Flexible schedule

Remote work

Freelance opportunities

Job summary

Alignerr Corp. is seeking a Wildlife and Habitat Conservation Scientist to contribute to AI training focused on biodiversity protection and ecosystem management.

This fully remote, flexible contract role offers 10–40 hours per week and the chance to work asynchronously on cutting-edge AI development. You will review AI-generated scenarios, assess ecological reasoning, and provide structured feedback to improve AI reliability.

Qualifications

• 3+ years in wildlife biology, ecology, habitat conservation or related field.
• Strong foundational knowledge of biodiversity and ecosystem management.
• Able to critically evaluate applied ecological reasoning presented in written form.
• Detail-oriented and comfortable reviewing structured scientific content at scale.
• Self-motivated and reliable when working independently.

Responsibilities

• Review AI-generated wildlife and habitat conservation scenarios for scientific accuracy.
• Assess quality of ecological reasoning and conservation strategies in AI outputs.
• Identify unrealistic assumptions, oversimplifications, or misapplied conservation methods.
• Provide clear, structured feedback to improve ecological validity of AI responses.
• Work independently and asynchronously to complete task-based assignments on your schedule.

Skills

Wildlife biology

Ecology

Habitat conservation

Critical evaluation

Independent work

Education

Graduate degree in Ecology

Job description

Alignerr Corp. is seeking a Wildlife and Habitat Conservation Scientist to contribute to AI training focused on biodiversity protection and ecosystem management.

This fully remote, flexible contract role offers 10–40 hours per week and the chance to work asynchronously on cutting-edge AI development. You will review AI-generated scenarios, assess ecological reasoning, and provide structured feedback to improve AI reliability.