AI Data Trainer – Environmental Engineering (Remote)

About the role

We are partnering with leading AI research labs to make large language models smarter and safer. As an AI Data Trainer you will apply your environmental engineering expertise to stress‑test AI models on real‑world problems, identify reasoning gaps, and create gold‑standard solutions that guide model development.

Key responsibilities

• Design complex, domain‑specific scenarios covering contaminant transport, mass‑balance calculations, hydrology, air‑quality modeling and life‑cycle assessments.
• Author detailed, step‑by‑step ground‑truth solutions, including chemical dosage, hydraulic flow and pollutant dispersion calculations.
• Audit AI‑generated remediation plans and impact statements for technical accuracy, regulatory compliance (EPA, ISO 14001) and safety.
• Provide structured feedback on AI reasoning errors such as incorrect stoichiometry or missed secondary impacts.
• Manage your own schedule and deliver work 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: aquatic chemistry, wastewater process design, air‑quality engineering or hazardous‑waste remediation.
• Excellent written communication of technical and ecological concepts.
• Highly detail‑oriented, especially with unit conversions, chemical equations and regulatory logic.
• No prior AI experience required; training will be provided.

Required skills

• AERMOD
• SWMM
• SimaPro

What we offer

• Fully remote, flexible schedule (10–40 hours/week).
• Freelance contract with hourly compensation.
• Opportunity to work alongside top AI researchers and gain hands‑on experience with advanced LLMs.
• Potential for ongoing work and contract extensions.