Environmental Engineering - AI Data Trainer

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

Job summary

Alignerr is seeking Environmental Engineering professionals to train AI with domain-specific problems in water treatment, air quality, remediation and compliance. You will craft challenging issues, develop benchmark solutions including dosage and flow models, and assess AI outputs for accuracy and safety.

The role emphasizes independent work on an asynchronous schedule, with remote collaboration and potential for ongoing engagement. Master’s or PhD preferred.

Qualifications

• Master's or PhD in Environmental Engineering or Civil Engineering (environmental focus).
• Strong knowledge in aquatic chemistry, wastewater design, air quality engineering or hazardous waste remediation.
• Excellent written communication of complex technical concepts.
• Meticulous with unit conversions, chemical equations and regulatory logic.

Responsibilities

• Design Advanced Engineering Problems spanning contaminant transport, mass balance, hydrology and LCA.
• Author precise, step-by-step technical solutions for AI benchmarking.
• Audit AI outputs, remediation plans and regulatory compliance with EPA/ISO 14001 standards.
• Document logical failures and provide feedback to improve model reasoning.

Skills

aquatic chemistry

wastewater design

air quality engineering

hazardous waste remediation

Education

Master's or PhD in Environmental Engineering or Civil Engineering (environmental focus)

Tools

AERMOD

EPANET

Job description

Environmental Engineering — AI Data Trainer

About The Role

We're partnering with the world's leading AI research labs to build smarter, more technically rigorous AI models — and we need environmental engineers to make it happen. This is a unique opportunity to apply your deep domain expertise in water treatment, air quality, remediation, and environmental compliance to directly shape how advanced AI systems reason through complex engineering problems. Your knowledge doesn't just support the work — it is the work.

• Organization: Alignerr
• Type: Hourly Contract
• Location: Remote
• Commitment: 10–40 hours/week

What You'll Do

• Design Advanced Engineering Problems — Craft challenging, domain-specific problems spanning contaminant transport, mass balance in treatment systems, hydrology, and Life Cycle Assessments (LCA) to rigorously test AI reasoning
• Author Gold-Standard Solutions — Develop precise, step-by-step technical solutions — including chemical dosage calculations, hydraulic flow models, and pollutant dispersion simulations — that serve as the benchmark for AI performance
• Audit AI Outputs — Evaluate AI-generated remediation plans, environmental impact statements, and engineering calculations for technical accuracy, safety, and regulatory compliance (EPA, ISO 14001, and similar standards)
• Sharpen AI Reasoning — Identify and document logical failures such as incorrect stoichiometry, flawed mass balances, or missed secondary environmental impacts, and provide structured feedback that directly improves model performance

Who You Are

• Currently pursuing or have completed a Master's or PhD in Environmental Engineering, Civil Engineering (environmental focus), or a closely related field
• Strong foundational knowledge in one or more of: aquatic chemistry, wastewater process design, air quality engineering, or hazardous waste remediation
• Able to communicate complex technical concepts clearly and precisely in writing
• Meticulous with unit conversions, chemical equations, and regulatory logic
• Self-directed and reliable — comfortable working independently on an async schedule
• No prior AI experience required

Nice to Have

• Experience with data annotation, quality assurance, or evaluation workflows
• Familiarity with environmental modeling software (e.g., AERMOD, EPANET, or similar)
• Background in regulatory compliance or environmental consulting

Why Join Us

• Work on the cutting edge of AI development alongside top research labs and teams
• Fully remote and flexible — set your own hours and work at your own pace
• Freelance autonomy: no micromanagement, no rigid schedules, global collaboration
• Make a direct, meaningful impact on how AI handles real-world environmental and engineering challenges
• Potential for ongoing work and contract extension based on performance