Environmental Engineering - AI Data Trainer
Posted 1 day ago by Alignerr
Negotiable
Undetermined
Remote
Glasgow, Scotland, United Kingdom
Summary: The role of Environmental Engineering – AI Data Trainer involves collaborating with leading AI research labs to enhance AI models through the application of environmental engineering expertise. The position requires designing complex environmental scenarios, authoring technical solutions, auditing AI outputs, and improving AI reasoning. Candidates will work independently on a flexible schedule, contributing to meaningful AI projects without needing prior AI experience. This is an opportunity to apply advanced engineering knowledge in a cutting-edge AI context.
Key Responsibilities:
- Design Complex Problems — Craft advanced environmental engineering scenarios across domains including contaminant transport, mass balance in treatment plants, hydrology, and Life Cycle Assessments (LCA)
- Author Gold-Standard Solutions — Develop rigorous, step-by-step technical solutions — chemical dosage calculations, hydraulic flow models, pollutant dispersion simulations — that serve as definitive reference answers
- Audit AI Outputs — Evaluate AI-generated remediation plans, environmental impact statements, and technical proofs for accuracy, safety, and alignment with regulatory standards (EPA, ISO 14001, and more)
- Improve AI Reasoning — Identify logical errors in AI responses — such as flawed stoichiometry in biological processes or missing secondary environmental impacts — and provide structured feedback that sharpens model thinking
- Work Independently — Complete assignments asynchronously on your own schedule with full flexibility
Key Skills:
- Pursuing or holding a Master's or PhD in Environmental Engineering, Civil Engineering (environmental focus), or a closely related field
- 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 in writing
- Precise and detail-oriented — especially around unit conversions, chemical equations, and regulatory compliance logic
- No prior AI or data annotation experience required
- Experience with data annotation, data quality assessment, or evaluation workflows (nice to have)
- Familiarity with environmental modeling software (e.g., AERMOD, SWMM, EPA tools) (nice to have)
- Background in EHS compliance or environmental impact assessment (nice to have)
Salary (Rate): £60.00 hourly
City: Glasgow
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 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 challenges, from contaminant transport to regulatory compliance. This is a rare opportunity to apply your graduate-level engineering knowledge in a cutting-edge AI context — no prior AI experience needed.
Organization: Alignerr
Type: Hourly Contract
Location: Remote
Commitment: 10–40 hours/week
What You'll Do
- Design Complex Problems — Craft advanced environmental engineering scenarios across domains including contaminant transport, mass balance in treatment plants, hydrology, and Life Cycle Assessments (LCA)
- Author Gold-Standard Solutions — Develop rigorous, step-by-step technical solutions — chemical dosage calculations, hydraulic flow models, pollutant dispersion simulations — that serve as definitive reference answers
- Audit AI Outputs — Evaluate AI-generated remediation plans, environmental impact statements, and technical proofs for accuracy, safety, and alignment with regulatory standards (EPA, ISO 14001, and more)
- Improve AI Reasoning — Identify logical errors in AI responses — such as flawed stoichiometry in biological processes or missing secondary environmental impacts — and provide structured feedback that sharpens model thinking
- Work Independently — Complete assignments asynchronously on your own schedule with full flexibility
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 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 in writing
- Precise and detail-oriented — especially around unit conversions, chemical equations, and regulatory compliance logic
- No prior AI or data annotation experience required
Nice to Have
- Experience with data annotation, data quality assessment, or evaluation 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 alongside top research labs and scientists
- Fully remote and flexible — work on your own schedule, anywhere in the world
- Gain firsthand exposure to how advanced large language models (LLMs) are trained and evaluated
- Freelance perks: autonomy, variety, and collaboration with a globally distributed team
- Potential for ongoing work and contract extension