Environmental Engineering - AI Data Trainer

Alignerr Corp.; United States; Remote; CAD 83,000 - 165,000; Full time

Benefits offered by this job

Fully remote work

Job summary

Alignerr Corp. seeks Environmental Engineering – AI Data Trainer to help train advanced AI models on environmental topics.

This fully remote hourly contract works with Alignerr and partners with leading AI research teams and labs. The role involves designing complex problems in environmental engineering, authoring rigorous step-by-step solutions, and auditing AI outputs for regulatory compliance and technical accuracy.

Qualifications

• Pursuing or holding a Master’s or PhD in Environmental Engineering, Civil Engineering (environmental focus), or a closely related field.
• Experience with data annotation, data quality review, or evaluation systems is nice to have.
• Familiarity with environmental modeling software such as AERMOD, SWMM, WASP is advantageous.

Responsibilities

• Design complex engineering problems spanning contaminant transport, mass balance in treatment plants, hydrology, LCA, and more.
• Author ground-truth solutions with step-by-step technical calculations and models for AI training.
• Audit AI outputs for technical accuracy, safety, and regulatory compliance (EPA, ISO 14001, etc.).
• Refine AI reasoning by identifying logical errors and providing structured feedback to improve model thinking.

Skills

Independent work capability

Data annotation familiarity

Education

Master's or PhD in Environmental Engineering

Tools

AERMOD

SWMM

WASP

Job description

Environmental Engineering – AI Data Trainer

About The Role

We're looking for environmental engineering experts to help train and improve advanced AI models on technically demanding topics. Your domain knowledge will directly shape how AI understands and reasons through real-world environmental challenges — from contaminant transport to regulatory compliance.

This is a fully remote, flexible contract role working with Alignerr, a company that partners with the world's leading AI research teams and labs.

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

What You'll Do

• Design Complex Engineering Problems — Develop advanced, multi-step problems spanning contaminant transport, mass balance in treatment plants, hydrology, Life Cycle Assessments (LCA), and more
• Author Ground-Truth Solutions — Write rigorous, step-by-step technical solutions — including chemical dosage calculations, hydraulic flow models, and pollutant dispersion simulations — that serve as benchmark responses for AI training
• Audit AI Outputs — Evaluate AI-generated remediation plans, environmental impact statements, and mathematical derivations for technical accuracy, safety, and regulatory compliance (EPA, ISO 14001, etc.)
• Refine AI Reasoning — Identify logical errors in AI reasoning — such as incorrect stoichiometry in biological treatment processes or failure to account for secondary environmental impacts — and provide structured feedback to improve model thinking

Who You Are

• Pursuing or holding 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 engineering concepts clearly and precisely in written form
• Meticulous with unit conversions, chemical equations, and regulatory compliance logic
• Self-motivated and comfortable working independently and asynchronously
• No prior AI experience required

Nice to Have

• Experience with data annotation, data quality review, or evaluation systems
• Familiarity with environmental modeling software (e.g., AERMOD, SWMM, WASP)
• Background in EHS compliance or environmental consulting

Why Join Us

• Work on cutting-edge AI projects alongside top AI research labs
• Fully remote and flexible — work on your schedule, as much or as little as you want
• Freelance perks: autonomy, variety, and global collaboration
• Gain rare insight into how large language models are trained and evaluated
• Meaningful work that advances how AI handles critical environmental and scientific topics
• Potential for ongoing work and contract extension