Environmental Engineering - AI Data Trainer
Posted Today by Alignerr
Negotiable
Undetermined
Remote
Oxford, England, United Kingdom
Summary: The role of Environmental Engineering – AI Data Trainer involves collaborating with leading AI research labs to enhance AI's understanding of environmental engineering topics. The position requires domain expertise to evaluate and refine AI models, focusing on real-world environmental issues. This is a fully remote, flexible contract role, allowing for a commitment of 10–40 hours per week. Candidates will engage in designing technical problems, authoring solutions, auditing AI outputs, and providing feedback to improve AI reasoning.
Key Responsibilities:
- Design Advanced Technical Problems — Craft challenging environmental engineering scenarios across domains including contaminant transport, mass balance in treatment systems, hydrology, and Life Cycle Assessments (LCA)
- Author Gold-Standard Solutions — Develop rigorous, step-by-step technical responses covering chemical dosage calculations, hydraulic flow models, and pollutant dispersion simulations that serve as reference benchmarks
- Audit AI Outputs — Critically evaluate AI-generated remediation plans, environmental impact statements, and mathematical proofs for technical accuracy, safety, and compliance with standards such as EPA regulations and ISO 14001
- Sharpen AI Reasoning — Identify logical errors in AI outputs and provide structured feedback to improve model thinking
Key Skills:
- Advanced Degree — Master's (pursuing or completed) or PhD in Environmental Engineering, Civil Engineering with an environmental focus, or a closely related discipline
- Deep Domain Knowledge — Strong foundational expertise in at least one of: aquatic chemistry, wastewater process design, air quality engineering, or hazardous waste remediation
- Clear Technical Communicator — Able to explain complex engineering and ecological concepts precisely and concisely in writing
- Precision-Oriented — High attention to detail when reviewing unit conversions, chemical equations, regulatory logic, and numerical calculations
- No AI experience required — if you know environmental engineering, we'll handle the rest
- Prior experience with data annotation, data quality, or evaluation workflows (Nice to Have)
- Familiarity with environmental modeling software (e.g., AERMOD, SWMM, EPA tools) (Nice to Have)
- Experience writing technical reports or regulatory documentation (Nice to Have)
Salary (Rate): £60.00 hourly
City: Oxford
Country: United Kingdom
Working Arrangements: remote
IR35 Status: undetermined
Seniority Level: undetermined
Industry: IT
Environmental Engineering – AI Data Trainer
About The Role
We're partnering with the world's leading AI research labs to build smarter, more accurate AI — and we need environmental engineers to make it happen. As an AI Data Trainer, you'll use your domain expertise to challenge, evaluate, and refine advanced language models on complex environmental engineering topics. Your technical knowledge directly shapes how AI reasons about real-world problems like contaminant transport, wastewater treatment, and regulatory compliance. This is a fully remote, flexible contract role — work on your schedule, on problems that matter.
Organization: Alignerr
Type: Hourly Contract
Location: Remote
Commitment: 10–40 hours/week
What You'll Do
- Design Advanced Technical Problems — Craft challenging environmental engineering scenarios across domains including contaminant transport, mass balance in treatment systems, hydrology, and Life Cycle Assessments (LCA)
- Author Gold-Standard Solutions — Develop rigorous, step-by-step technical responses covering chemical dosage calculations, hydraulic flow models, and pollutant dispersion simulations that serve as reference benchmarks
- Audit AI Outputs — Critically evaluate AI-generated remediation plans, environmental impact statements, and mathematical proofs for technical accuracy, safety, and compliance with standards such as EPA regulations and ISO 14001
- Sharpen AI Reasoning — Identify logical errors in AI outputs — such as incorrect stoichiometry in biological processes or failure to account for secondary environmental impacts — and provide structured feedback to improve model thinking
Who You Are
- Advanced Degree — Master's (pursuing or completed) or PhD in Environmental Engineering, Civil Engineering with an environmental focus, or a closely related discipline
- Deep Domain Knowledge — Strong foundational expertise in at least one of: aquatic chemistry, wastewater process design, air quality engineering, or hazardous waste remediation
- Clear Technical Communicator — Able to explain complex engineering and ecological concepts precisely and concisely in writing
- Precision-Oriented — High attention to detail when reviewing unit conversions, chemical equations, regulatory logic, and numerical calculations
- No AI experience required — if you know environmental engineering, we'll handle the rest
Nice to Have
- Prior experience with data annotation, data quality, or evaluation workflows
- Familiarity with environmental modeling software (e.g., AERMOD, SWMM, EPA tools)
- Experience writing technical reports or regulatory documentation
Why Join Us
- Work on some of the most advanced AI projects in the world, alongside top research labs
- Fully remote and async — structure your work around your life
- Freelance autonomy with the opportunity to work on genuinely challenging, intellectually stimulating problems
- Apply your environmental expertise in a high-impact, emerging field
- Potential for ongoing work and contract extension