Environmental Engineering - AI Data Trainer

About the role

We are seeking experienced environmental engineering professionals to train and improve next‑generation AI models. Your expertise will shape how AI tackles complex water‑treatment, air‑quality, remediation and compliance challenges, delivering real‑world impact.

Key responsibilities

• Design advanced, real‑world environmental engineering scenarios covering contaminant transport, mass‑balance, hydrology and life‑cycle assessments.
• Author rigorous ground‑truth solutions with detailed calculations, hydraulic models and pollutant dispersion simulations.
• Audit AI‑generated remediation plans, impact statements and engineering calculations for technical accuracy, safety and regulatory compliance (EPA, ISO 14001).
• Identify logical flaws in model reasoning and provide structured feedback to improve AI decision‑making.
• Collaborate directly on tasks that enhance AI safety, reliability and performance for environmental applications.

Required profile

• Pursuing or holding a Master’s or PhD in Environmental Engineering, Civil Engineering (environmental focus) or a related discipline.
• Strong knowledge in at least one area such as aquatic chemistry, wastewater process design, air‑quality engineering, hazardous waste remediation or EHS compliance.
• Excellent written communication of complex technical concepts.
• Detail‑oriented with precise unit conversions, chemical equations and regulatory logic.
• Self‑motivated, able to work independently and asynchronously.
• No prior AI experience required.

Required skills

• Aquatic chemistry
• Wastewater process design
• Air‑quality engineering
• Hazardous waste remediation
• EHS compliance and regulatory standards (EPA, ISO 14001)
• Unit conversion and chemical equation balancing
• Data annotation and data‑quality review
• Familiarity with environmental modelling software such as AERMOD, MODFLOW, SimaPro

What we offer

• Fully remote, flexible schedule (10–40 hours per week).
• Freelance autonomy – choose your hours and work from anywhere.
• Opportunity to work with leading AI research labs and gain insight into large‑language‑model training.
• Meaningful work that improves AI reliability in high‑stakes environmental domains.