Environmental Engineering — AI Data Trainer About The Role We're partnering with the world's leading AI research labs to build smarter, more technically rigorous AI models — and we need environmental engineers to make it happen. Your domain expertise will directly shape how AI understands and reasons through complex environmental problems, from contaminant transport modeling to regulatory compliance. This is a unique opportunity to contribute to cutting-edge AI development without leaving your field. No AI experience required — just deep environmental engineering knowledge and a sharp analytical mind.
Organization: Alignerr
Type: Hourly Contract
Location: Remote
Commitment: 10–40 hours/week
What You'll Do
Design Advanced Problems — Develop technically rigorous environmental engineering challenges spanning contaminant transport, mass balance in treatment plants, hydrology, and Life Cycle Assessments (LCA)
Author Ground-Truth Solutions — Write detailed, step-by-step technical solutions — including chemical dosage calculations, hydraulic flow models, and pollutant dispersion simulations — that serve as gold-standard reference answers
Audit AI Outputs — Critically evaluate AI-generated remediation plans, environmental impact statements, and engineering calculations for technical accuracy, safety, and regulatory compliance (EPA, ISO 14001, and others)
Sharpen AI Reasoning — Identify logical errors in AI responses — such as incorrect stoichiometry, flawed mass balances, or missed secondary environmental impacts — and provide structured feedback to improve model performance
Who You Are
Holds or is pursuing a Master's or PhD in Environmental Engineering, Civil Engineering (with environmental focus), or a closely related discipline
Strong foundational knowledge in one or more of: aquatic chemistry, wastewater process design, air quality engineering, or hazardous waste remediation
Able to communicate complex technical and ecological concepts clearly in writing
High attention to detail — especially with unit conversions, chemical equations, and regulatory logic
Self-motivated and comfortable working independently and asynchronously
No prior AI experience required
Nice to Have
Experience with data annotation, quality evaluation, or technical review workflows
Familiarity with environmental modeling software (e.g., AERMOD, SWMM, EPA tools)
Background in EHS compliance or environmental impact assessment
Why Join Us
Work on meaningful AI projects with top-tier research labs and teams
Fully remote and flexible — set your own schedule and workload
Bring your real-world expertise to a field that rarely gets deep technical scrutiny
Gain exposure to how advanced large language models (LLMs) are trained and evaluated
Freelance perks: autonomy, variety, and global collaboration
Potential for ongoing work and contract extension
Skills
Education and TrainingTechnology, Information and Internet