Environmental Engineering - AI Data Trainer

Environmental Engineering - AI Data Trainer

Join to apply for the Environmental Engineering - AI Data Trainer role at Alignerr
.

$35.00/hr - $60.00/hr

Location:

Remote

At Alignerr, we partner with the world’s leading AI research teams and labs to build and train cutting‑edge AI models.

You’ll challenge advanced language models on topics such as water and wastewater treatment, air quality management, EHS and compliance, and solid and hazardous waste management—documenting every failure mode so we can harden model reasoning.

Organization:
Alignerr Position:
Environmental Engineering - AI Data Trainer Type:
Hourly Contract Compensation: $35–$60 /hour

Location:

Remote Commitment: 10–40 hours/week

• Design advanced environmental engineering problems across domains such as contaminant transport, mass balance in treatment plants, hydrology, and Life Cycle Assessments (LCA).
• Create rigorous, step‑by‑step technical solutions—chemical dosage calculations, hydraulic flow models, pollutant dispersion simulations—that serve as "golden responses."
• Evaluate AI‑generated remediation plans, environmental impact statements, and mathematical proofs for technical accuracy, safety, and adherence to regulatory standards (e.g., EPA, ISO 14001).
• Identify logical fallacies in AI reasoning—such as incorrect stoichiometry in biological processes or failure to account for secondary environmental impacts—and provide structured feedback to improve model reasoning.

• Advanced degree:
  Master’s (pursuing or completed) or PhD in Environmental Engineering, Civil Engineering (with an environmental focus), or a closely related field.
• Domain expertise in aquatic chemistry, wastewater process design, air quality engineering, or hazardous waste remediation.
• Strong analytical writing skills—ability to communicate complex ecological and engineering concepts clearly and concisely.
• Attention to detail—expertise in unit conversions (mg/L to ppm), chemical equations, and regulatory compliance logic.
• No AI experience required.

• Prior experience with data annotation, data quality, or evaluation systems.
• Familiarity with environmental modeling software.

• Competitive pay and flexible remote work.
• Collaborate with a team working on cutting‑edge AI projects.
• Exposure to advanced LLMs and their training processes.
• Freelance perks: autonomy, flexibility, and global collaboration.
• Potential for contract extension.

• Submit your resume.
• Complete a short screening.
• Project matching and onboarding.