Aerospace CAD Question Authoring Expert

The work

You will help train AI systems by studying detailed, multi-part aerospace assemblies and turning their technical information into clear questions and accurate answers. The work focuses on exact interpretation of design features, functions, and relationships between components.

You will also communicate in writing and occasional verbal discussions, contribute to documentation, and provide feedback that improves future question sets and project workflows.

• Review FreeCAD-format files and analyze complex mechanical assemblies.
• Write several objective, non-guessable questions for each assembly.
• Create clear answers grounded in the assembly data.
• Cover important features, functions, and relationships between parts.
• Help improve documentation, question sets, and project workflows.

What it pays and takes

This is a remote, part-time contractor role. The work requires aerospace, mechanical engineering, or industrial design knowledge, along with the ability to interpret complex designs and communicate technical details clearly.

• Pay: $40 to $80 per hour.
• Work type: Remote, part-time contract work.
• Language: Professional fluency in English.
• Location: Open to candidates in listed countries across the Americas, Europe, Asia, Africa, and the Middle East.
• Required: Expertise in aerospace, mechanical engineering, or industrial design.
• Required: Strong CAD knowledge and hands-on experience with multi-part assemblies.
• Required: Ability to interpret design intent and technical drawings.
• Required: Ability to write precise, concise technical questions and answers.
• Required: Strong attention to detail and excellent written and verbal communication.
• Helpful: FreeCAD or similar CAD platform experience, plus educational or documentation writing experience.
• Prior AI training experience is not required.

How it works

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

About AI training work

AI training is the human work behind systems that learn from examples. Contributors write, review, and rate material so AI systems can produce more accurate and useful results, while people with specialist knowledge help assess technical subjects.