Remote Environmental AI Data Trainer (Contract)

Alignerr Corp.; Adelaide; Remote; AUD 83,000 - 131,000; Part time

Benefits offered by this job

Autonomy

Variety

Global network of experts

Job summary

Alignerr seeks an Environmental Engineer to train AI data for environmental scenarios. This remote hourly contract lets you work 10–40 hours per week, applying your domain knowledge to improve AI understanding of contaminant transport, regulatory compliance, and environmental modeling.

You'll design problems, author solutions, and audit AI outputs, collaborating with a global network of experts. No AI background is required, making it accessible to driven environmental engineers seeking flexible

Qualifications

• Pursuing/holding a Master's or PhD in Env. Engineering or Civil Eng (Environmental focus).
• Strong foundation in aquatic chemistry, wastewater design, air quality, or hazardous waste remediation.
• Able to communicate complex concepts clearly in writing.
• Highly precise—you catch unit conversions and regulatory gaps.
• Self-motivated and able to work independently and asynchronously.
• No prior AI experience required.

Responsibilities

• Design advanced technical problems for AI training across environmental topics.
• Author ground-truth solutions with step-by-step calculations.
• Audit AI outputs for regulatory adherence and technical accuracy.
• Refine AI reasoning and document model failures with feedback.
• Stress-test models across water, air, and waste domains.

Skills

Aquatic chemistry

Wastewater design

Air quality engineering

Hazardous waste remediation

Technical writing

Independent work

Education

Master's or PhD in Environmental Eng./Civil Eng (env)

Tools

AERMOD

SWMM

Job description

Alignerr seeks an Environmental Engineer to train AI data for environmental scenarios. This remote hourly contract lets you work 10–40 hours per week, applying your domain knowledge to improve AI understanding of contaminant transport, regulatory compliance, and environmental modeling.

You'll design problems, author solutions, and audit AI outputs, collaborating with a global network of experts. No AI background is required, making it accessible to driven environmental engineers seeking flexible