Civil, Geotechnical & Structural Field Engineer (English)

You will create realistic technical problems that test and train advanced AI models. Your work will draw on site and monitoring data such as settlement records, pile and load tests, inspection reports, and instrumentation readings.

You will use your own field data and engineering experience to produce accurate, clear, and well-documented problems. The work is task-based, fully remote, and independent.

• Write research-level problems in civil, geotechnical, or structural field engineering.
• Use site and monitoring data to build accurate, realistic problems.
• Work with data in Python or a similar programming language.
• Write clearly about technical work in your field.

What it pays and takes

This is flexible independent-contractor work. There is no fixed weekly schedule and no cap on the number of tasks you can take on.

• $50 per hour equivalent, paid per approved task that meets project specifications.
• Each approved task pays $300 and takes about six hours.
• Fully remote work with flexible scheduling.
• Open to candidates in the countries listed for this role.
• Fluent in English.
• Hands-on experience working with your own site and monitoring data in Python or a similar language.
• Able to work independently and manage your own time.
• Able to work as an independent contractor without visa sponsorship.
• Helpful background includes three or more years working with field data and a degree in civil engineering.
• Back-analysis of monitoring data, pile load test interpretation, or a PE or Chartered Engineer credential is helpful.
• Public code, a thesis, or papers showing your technical work are helpful.
• Prior data annotation, data labeling, or AI and machine learning evaluation experience is helpful.

How it works

Apply on OpenTrain with your resume, then complete the application on the hiring site. Accepted experts undergo standard background and identity verification.

About AI training work

AI training work is the human work behind artificial intelligence. Contributors create and review examples, including written problems and model responses, so AI systems can learn from accurate, useful material.

People with strong technical experience are paid for applying their subject knowledge and judgment to this work.