Environmental Engineering – AI Data Trainer

About The Role

We're partnering with the world's leading AI research labs to build smarter, safer AI — and we need environmental engineers to help get it right. As an AI Data Trainer, you'll stress-test advanced language models on complex environmental engineering problems, expose their weaknesses, and help shape how AI reasons through real-world technical challenges.

This is a rare opportunity to apply your deep domain expertise in a high-impact, forward-looking role — without leaving your home office.

Organization: Alignerr Type: Hourly Contract Location: Remote Commitment: 10–40 hours/week

What You'll Do

Design Complex Problems — Craft advanced environmental engineering challenges spanning contaminant transport, wastewater treatment mass balances, hydrology, air quality modeling, and Life Cycle Assessments (LCA) Author Ground-Truth Solutions — Develop rigorous, step-by-step technical solutions — including chemical dosage calculations, hydraulic flow models, and pollutant dispersion simulations — that serve as definitive reference answers Audit AI Outputs — Critically evaluate AI-generated remediation plans, environmental impact statements, and regulatory compliance analyses for technical accuracy and adherence to standards such as EPA regulations and ISO 14001 Refine AI Reasoning — Identify logical flaws in model responses (e.g., incorrect stoichiometry, overlooked secondary impacts) and provide structured, expert feedback that directly improves how AI thinks through environmental problems

Who You Are

Pursuing or holding 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, or hazardous waste remediation Able to communicate complex technical and ecological concepts clearly and precisely in writing Meticulous with unit conversions, chemical equations, and regulatory compliance logic No prior AI experience required — your engineering expertise is what matters

Nice to Have

Experience with data annotation, data quality review, or evaluation systems Familiarity with environmental modeling software (e.g., AERMOD, SWMM, or similar tools) Background in EHS compliance or environmental consulting

Why Join Us

Work on cutting-edge AI projects alongside top research labs and AI teams Fully remote and flexible — work on your own schedule, 10–40 hours per week Gain hands-on exposure to how large language models (LLMs) are trained and evaluated Freelance perks: autonomy, variety, and collaboration with a global network of experts Meaningful work — your contributions directly improve how AI handles real-world environmental challenges Potential for ongoing work and contract extension