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