AI Data Trainer – Environmental Engineering

About the role

We are partnering with leading AI research labs to improve large language models on real‑world environmental engineering challenges. As an AI Data Trainer you will design, solve, and evaluate technical problems that help make AI outputs more accurate, safe, and compliant.

Key responsibilities

• Design complex engineering scenarios covering contaminant transport, wastewater treatment, hydrology, air‑quality modeling and life‑cycle assessment.
• Author detailed, 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 correctness, regulatory compliance (EPA, ISO 14001) and safety.
• Identify logical flaws in AI reasoning and provide structured feedback to improve model performance.
• Work independently, managing your own schedule and delivering tasks asynchronously.

Required profile

• Currently pursuing or holding a Master’s or PhD in Environmental Engineering, Civil Engineering (environmental focus) or a closely related discipline.
• Strong knowledge in at least one core area such as aquatic chemistry, wastewater process design, air‑quality engineering or hazardous‑waste remediation.
• Excellent written communication of complex technical and ecological concepts.
• Detail‑oriented with high precision in unit conversions, chemical equations and regulatory logic.
• No prior AI experience required; training will be provided.

Required skills

• AERMOD
• SWMM
• SimaPro
• Data annotation and data‑quality evaluation workflows
• Environmental impact assessment

What we offer

• Fully remote, flexible schedule (10–40 hours/week).
• Freelance autonomy with exposure to cutting‑edge large language models.
• Collaboration with top research labs and scientists.
• Potential for ongoing work and contract extensions.