Environmental Engineering, AI Data Trainer
Alignerr
Miami, FLFresher1h agovia LinkedIn
This job at a glance
- Who can apply
- New grads, no experience needed
- Must know
- Auditing
- Work
- On-site in Miami
- Pay
- Not stated by the employer.
- Skill demand
- Auditing1%of 93 similar entry-level jobs posted in the US this week
- Listed
- Oct 30, 2026 · still open
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About the Role
Alignerr is partnering with leading AI research teams to build smarter, more technically rigorous AI models. As an AI Data Trainer, you will leverage your domain knowledge to stress-test and improve how advanced language models reason through real-world environmental engineering problems. Your expertise will directly shape the reliability of AI systems used by engineers, researchers, and policymakers worldwide.
- Organization: Alignerr
- Type: Hourly Contract
- Location: Remote
- Commitment: 10–40 hours/week
Key Responsibilities
- Design Advanced Technical Problems: Create challenging environmental engineering scenarios spanning contaminant transport, mass balance in treatment plants, hydrology, Life Cycle Assessments (LCA), and more.
- Author Gold-Standard Solutions: Develop rigorous, step-by-step technical solutions, including chemical dosage calculations, hydraulic flow models, and pollutant dispersion simulations, to serve as benchmark responses for AI training.
- Audit AI Outputs: Critically evaluate AI-generated remediation plans, environmental impact statements, and technical calculations for accuracy, safety, and regulatory compliance (e.g., EPA, ISO 14001).
- Sharpen AI Reasoning: Identify where AI reasoning breaks down (e.g., incorrect stoichiometry, missed secondary impacts, flawed unit conversions) and provide structured feedback to improve model performance.
Requirements & Tech Stack
- 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.
- Ability to communicate complex technical and ecological concepts clearly and precisely in written form.
- Detail-oriented with meticulous attention to unit conversions, chemical equations, and regulatory logic.
- Self-motivated and comfortable working independently on technically demanding tasks.
- No prior AI experience required.
Nice to Have
- Experience with data annotation, data quality review, or evaluation systems.
- Familiarity with environmental modeling software (e.g., AERMOD, SWMM, or similar).