CAD Tool Specialist (AI Evaluation)

You will create realistic computer-aided design tasks that reflect professional workflows, then assess how well AI models handle them. Your feedback will explain what is technically accurate and what needs improvement.

• Create challenging CAD tasks based on practical workflows and professional design standards.
• Develop or assess 2D drafting, dimensioning, parametric modeling, constraint-based modeling, and scripted solid modeling.
• Review assemblies and exports for 3D printing, CNC machining, and laser cutting.
• Evaluate AI-generated responses for technical quality and accuracy.
• Give clear, structured written feedback about your decisions.

What it pays and takes

This is a remote, ongoing, project-based contractor opportunity that can be completed alongside another role. Work is self-paced with no set schedule.

• Pay: up to $125 per hour.
• Time: 20+ hours per week.
• Location: open to candidates in the United States.
• Education: a bachelor's degree or higher in mechanical engineering, architecture, industrial design, civil engineering, or a related field.
• Experience: at least two years of professional experience with LibreCAD, SolveSpace, OpenSCAD, or Rhino3D.
• Strong written communication and careful attention to detail.
• Ability to explain complex CAD and design concepts clearly.
• Ability to work independently in a remote, asynchronous setting.
• Helpful experience includes FreeCAD, Fusion 360, SolidWorks, AutoCAD, GD&T, technical drawing standards, scripting, and programmatic design.
• Professional experience in manufacturing, architecture, engineering, or product design, or a portfolio of published or fabricated designs, can support your application.

How it works

Apply on OpenTrain with your resume, then complete the application on the hiring site.

About AI training work

AI training is the human work behind systems that learn from examples, including reviewing model responses and rating their quality. People with practical CAD and design experience help models produce more accurate work by creating realistic tasks and explaining why an answer succeeds or fails.