Environmental Engineering - AI Data Trainer

About the Role

We're partnering with the world's leading AI research labs to make AI smarter — and we need environmental engineers to help get there. As an AI Data Trainer specializing in environmental engineering, you'll stress-test advanced AI models on complex technical problems, expose their reasoning gaps, and help build systems that can think like a domain expert.

What You'll Do

• Design Challenging Problems — Develop advanced environmental engineering scenarios spanning contaminant transport, mass balance in treatment plants, hydrology, pollutant dispersion, and Life Cycle Assessments (LCA)
• Author Expert-Level Solutions — Write rigorous, step-by-step technical solutions — including chemical dosage calculations, hydraulic flow models, and remediation plans — that serve as ground-truth benchmarks for AI training
• Audit AI Outputs — Evaluate AI-generated environmental impact statements, remediation strategies, and engineering calculations for technical accuracy, safety, and regulatory compliance (EPA, ISO 14001, and more)
• Sharpen AI Reasoning — Identify logical errors such as incorrect stoichiometry, flawed unit conversions, or failure to account for secondary environmental impacts, and provide structured feedback to improve model performance
• Work Independently — Complete task-based assignments asynchronously on a schedule that works for you

Who You Are

• Holds or is pursuing a Master's or PhD in Environmental Engineering, Civil Engineering (environmental focus), or a closely related discipline
• Strong foundational knowledge in one or more core areas: aquatic chemistry, wastewater process design, air quality engineering, hazardous waste remediation, or environmental compliance
• Precise and detail-oriented — you catch unit conversion errors, chemical equation imbalances, and regulatory inconsistencies that others miss
• Able to communicate complex engineering concepts clearly and concisely in writing
• Self-motivated and comfortable working independently on technical tasks
• No prior AI experience required

Nice to Have

• Experience with data annotation, data quality, or technical evaluation workflows
• Familiarity with environmental modeling software (e.g., AERMOD, SWMM, MODFLOW)
• Background in EHS compliance, regulatory consulting, or environmental auditing

Why Join Us

• Work on cutting-edge AI projects alongside top AI research labs and teams
• Fully remote and flexible — set your own hours and work from anywhere
• Freelance perks: autonomy, variety, and the chance to collaborate with a global network of experts
• Gain firsthand exposure to how large language models (LLMs) are trained and evaluated
• Make a meaningful impact — your expertise directly improves how AI handles real-world environmental engineering challenges
• Potential for ongoing work and contract extension