Environmental Engineering – AI Data Trainer

About the role

We are seeking experienced environmental engineers to help train and evaluate advanced AI models that address water and wastewater treatment, air quality, hazardous waste remediation, and compliance challenges. This fully remote, flexible contract lets you work 10–40 hours per week, shaping how AI interprets real‑world engineering problems.

Key responsibilities

• Design complex, domain‑specific engineering problems covering contaminant transport, mass balance, hydrology, and life‑cycle assessments.
• Author rigorous, step‑by‑step ground‑truth solutions, including chemical dosage calculations, hydraulic flow models, and pollutant dispersion simulations.
• Audit AI‑generated remediation plans, impact statements, and mathematical proofs for technical accuracy, regulatory compliance, and safety.
• Identify logical errors in AI reasoning (e.g., incorrect stoichiometry, missed secondary impacts) and provide structured feedback to improve model performance.

Required profile

• Pursuing or holding a Master’s or PhD in Environmental Engineering, Civil Engineering with an environmental focus, or a related discipline.
• Strong knowledge in at least one area such as aquatic chemistry, wastewater process design, air quality engineering, or hazardous waste remediation.
• Excellent written communication of technical and ecological concepts.
• Detail‑oriented with a knack for spotting unit conversion errors, flawed equations, and regulatory gaps.
• No prior AI experience required; training will be provided.

Required skills

• Familiarity with environmental modeling software (e.g., SWMM, AERMOD, EPA models).
• Experience with data annotation, data quality assurance, or evaluation workflows.

What we offer

• Fully remote, asynchronous work schedule.
• Freelance contract with autonomy, variety, and global collaboration.
• Hands‑on exposure to large language model training and evaluation.
• Potential for ongoing work and contract extensions.