$50–100/hr
The role in one line
A professional engineer who designs realistic civil engineering problems to evaluate and train AI models.
Written by Training Turk from the public listing; it may be incomplete or out of date. Read the full posting on micro1.
What you would do
- Create complex evaluation tasks in structural, transportation, water, and site development domains
- Source or generate technical documents such as drawings, specs, and regulatory references
- Build detailed rubrics that score solutions for code compliance and constraint satisfaction
- Generate and validate realistic engineering datasets in CSV and PDF formats
Who they are looking for
- Minimum five years of diverse civil engineering project experience
- Professional Engineer licensure or equivalent pursuit highly valued
- Expertise in code compliance and technical documentation management
- Ability to work independently and meet output-based submission targets
Skills this role asks for
What the interview is likely to probe
1.Problem design reflecting real constraints
AI models learn from how engineers actually reason through conflicting requirements, so your scenarios must capture genuine tradeoffs.
Expect something like: “Design a bridge routing task where environmental impact, soil conditions, and traffic volume create genuine competing demands that different engineers might resolve differently.”
2.Code compliance verification
Solutions may meet geometric and cost constraints but fail regulatory standards; you catch these misses.
Expect something like: “An AI proposed a foundation design that satisfies settlement limits but misses seismic code requirements for the region. What rubric item catches this error?”
3.Rubric clarity and scoring precision
Vague rubrics confuse models and evaluators alike; your criteria must be specific enough to grade consistently across dozens of submissions.
Expect something like: “Write rubric items for a water system design task that distinguish between a solution meeting code minimums versus one optimized for long-term maintenance costs.”
4.Document curation and authenticity
Models train better on realistic materials that engineers actually encounter in practice.
Expect something like: “Gather or generate the technical documents an engineer would realistically reference for a site in a steep slope zone with contaminated soil history.”
5.Error detection in proposed solutions
You verify that the correct answer is genuinely correct, catching mistakes that would otherwise train models on flawed reasoning.
Expect something like: “Review three proposed answers to a geotechnical design problem: one has the right approach but wrong pile depth, one correct, one uses outdated construction methods. Classify each.”
Exercise you may get
Author a complete water systems task: write the scenario, source or generate two supporting documents, specify the engineering solution, and create a rubric with at least four grading criteria.
How to prepare
- Assemble examples of real project documents from your portfolio that illustrate typical deliverables
- Review current versions of relevant building codes and standards
- Practice writing clear rubric criteria that separate surface answers from sound engineering
- Prepare a portfolio sample showing your technical documentation skills
Facts
- Pay
- $50–100/hr
- Eligible locations
- Bangladesh, Hong Kong, India, Indonesia, Japan, Kazakhstan, Kyrgyzstan, Malaysia, Pakistan, Philippines, Singapore, Sri Lanka, Taiwan, Thailand, Uzbekistan, Vietnam, Austria, Belarus, Belgium, Denmark, France, Germany, Greece, Italy, Netherlands, Portugal, Russia, Spain, Switzerland, United Kingdom, Argentina, Brazil, Chile, Colombia, Mexico, Peru, Algeria, Bahrain, Egypt, Iraq, Jordan, Kuwait, Lebanon, Libya, Morocco, Oman, Palestine, Qatar, Saudi Arabia, Tunisia, United Arab Emirates, United States, Canada, Nigeria, Kenya, South Africa, Ghana, Ethiopia
- Domain
- Applied Engineering
- Role type
- generalist
- Posted
- 9/16/2026
- Open slots
- 50