Environmental Engineering - AI Data Trainer
About this role
About the Role We're partnering with the world's leading AI research labs to make cutting-edge language models smarter, safer, and more technically rigorous — and we need environmental engineers to help us do it. As an AI Data Trainer, you'll stress-test advanced AI models on real-world environmental engineering problems, expose gaps in their reasoning, and author the gold-standard solutions that shape how these models think. Your domain expertise will directly influence the next generation of AI. - Organization: Alignerr - Type: Hourly Contract - Location: Remote - Commitment: 10–40 hours/week What You'll Do - Design Challenging Problems — Craft complex, domain-specific engineering scenarios spanning contaminant transport, mass balance in treatment plants, hydrology, air quality modeling, and Life Cycle Assessments (LCA) - Author Ground-Truth Solutions — Develop rigorous, step-by-step technical responses — including chemical dosage calculations, hydraulic flow models, and pollutant dispersion simulations — that serve as the benchmark for AI outputs - Audit AI Responses — Critically evaluate AI-generated remediation plans, environmental impact statements, and mathematical proofs for technical accuracy, regulatory compliance (EPA, ISO 14001), and safety - Improve AI Reasoning — Identify flaws in AI logic — such as incorrect stoichiometry in biological processes or overlooked secondary environmental impacts — and deliver structured feedback that sharpens model performance - Work Independently — Manage your own schedule, take on tasks asynchronously, and contribute meaningfully on your own terms Who You Are - Pursuing or holding a Master's or PhD in Environmental Engineering, Civil Engineering (environmental focus), or a closely related field - Strong foundational knowledge in at least one core area: aquatic chemistry, wastewater process design, air quality engineering, or hazardous waste remediation - Able to communicate complex technical and ecological concepts clearly in writing - Detail-oriented with precision when handling unit conversions, chemical equations, and regulatory logic - No prior AI experience required — we'll show you everything you need to get started Nice to Have - Experience with data annotation, data quality, or evaluation workflows - Familiarity with environmental modeling software (e.g., AERMOD, SWMM, SimaPro) - Background in EHS compliance or environmental impact assessment Why Join Us - Work on meaningful AI projects alongside top research labs and scientists - Fully remote and flexible — work when and where it suits you - Gain firsthand exposure to advanced large language models (LLMs) and how they're trained - Freelance perks: autonomy, variety, and global collaboration - Potential for ongoing work and contract extension
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