Environmental Engineering - AI Data Trainer

Environmental Engineering - AI Data Trainer

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This range is provided by Alignerr. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

$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 like 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

• Develop Complex Problems:
  Design advanced environmental engineering problems across domains like contaminant transport, mass balance in treatment plants, hydrology, and Life Cycle Assessments (LCA).
• Author Ground-Truth Solutions:
  Create rigorous, step-by-step technical solutions, including chemical dosage calculations, hydraulic flow models, and pollutant dispersion simulations that serve as "golden responses."
• Technical Auditing:
  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).
• Refine Reasoning:
  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 the model's "thinking" process.

• Advanced Degree:
  Masters (pursuing or completed) or PhD in Environmental Engineering, Civil Engineering (with an environmental focus), or a closely related field.
• Domain Expertise:
  Strong foundational knowledge in core areas such as aquatic chemistry, wastewater process design, air quality engineering, or hazardous waste remediation.
• Analytical Writing:
  The ability to communicate complex ecological and engineering concepts clearly and concisely in written form.
• Attention to Detail:
  High level of precision when checking unit conversions (e.g., 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 how they’re trained.
• Freelance perks: autonomy, flexibility, and global collaboration.
• Potential for contract extension.

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

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