Environmental Engineering - AI Data Trainer
About the role
We're partnering with the world's leading AI research labs to make AI smarter in specialized technical domains — and we need environmental engineers to help get it right. As an Environmental Engineering AI Data Trainer, you'll stress-test advanced language models on complex, real-world problems across water treatment, air quality, hazardous waste, and environmental compliance. Your expertise will directly shape how the next generation of AI reasons through environmental engineering challenges.
Responsibilities
- Design Complex Problems — Craft advanced environmental engineering scenarios spanning contaminant transport, mass balance in treatment plants, hydrology, Life Cycle Assessments (LCA), and more
- Author Gold-Standard Solutions — Write rigorous, step-by-step technical solutions — including chemical dosage calculations, hydraulic flow models, and pollutant dispersion simulations — that serve as benchmarks for AI responses
- Audit AI Outputs — Critically evaluate AI-generated remediation plans, environmental impact statements, and mathematical proofs for technical accuracy, regulatory compliance, and safety
- Sharpen AI Reasoning — Identify logical errors in AI outputs — such as incorrect stoichiometry, missing secondary impacts, or regulatory misapplications — and provide structured feedback to improve model reasoning
Requirements
Advanced Degree — Pursuing or holding a Master's or PhD in Environmental Engineering, Civil Engineering (environmental focus), or a closely related field
Domain Expertise — Strong foundational knowledge in areas such as aquatic chemistry, wastewater process design, air quality engineering, or hazardous waste remediation
Analytical Communicator — Able to explain complex ecological and engineering concepts clearly and precisely in writing
Detail-Oriented — Meticulous when checking unit conversions (e.g., mg/L to ppm), chemical equations, and regulatory compliance logic
No AI experience required — your engineering expertise is what matters
Nice to Have
- Prior experience with data annotation, quality evaluation, or review systems
- Familiarity with environmental modeling software (e.g., SWMM, AERMOD, GoldSim)
- Knowledge of regulatory frameworks such as EPA standards or ISO 14001
Qualifications
Advanced Degree — Pursuing or holding a Master's or PhD in Environmental Engineering, Civil Engineering (environmental focus), or a closely related field
Domain Expertise — Strong foundational knowledge in areas such as aquatic chemistry, wastewater process design, air quality engineering, or hazardous waste remediation
Analytical Communicator — Able to explain complex ecological and engineering concepts clearly and precisely in writing
Detail-Oriented — Meticulous when checking unit conversions (e.g., mg/L to ppm), chemical equations, and regulatory compliance logic
No AI experience required — your engineering expertise is what matters
Nice to Have
- Prior experience with data annotation, quality evaluation, or review systems
- Familiarity with environmental modeling software (e.g., SWMM, AERMOD, GoldSim)
- Knowledge of regulatory frameworks such as EPA standards or ISO 14001