Mechanical and Hardware Design Engineer for AI Evaluation

You will help evaluate how AI systems handle demanding mechanical and hardware design problems. The work focuses on your existing expertise rather than production engineering.

You will create realistic technical materials, write expert reference solutions, set grading standards, and review AI-generated answers. You will also explain your judgments through clear technical feedback and structured written analysis.

• Design realistic scenarios and problem sets for mechanical and hardware design applications.
• Create reference solutions that show technically sound reasoning.
• Write rubrics that separate correct, incomplete, and exceptional responses.
• Evaluate AI outputs for correctness, depth, and sound domain judgment.
• Provide structured written feedback on technical decisions.

This is a remote, independent, asynchronous expert engagement designed to fit around existing work.

• Pay: $135 per hour.
• Location: Remote and open to candidates in the countries specified for this role.
• Language: Fluent in English.
• Experience: Eight to twelve years in mechanical or hardware design, including CAD, RTL, robotics, or related hardware work.
• Education: A bachelor's degree is required.
• Helpful qualifications: A professional engineering license or master's degree.
• You should be currently or recently active in hands-on professional work.
• You need strong written communication skills and the ability to work independently and asynchronously.
• Experience reviewing, grading, editing, or giving peer feedback on technical work is useful.
• Research publications, open-source contributions, or recognized hardware work products are valuable.
• Relevant capabilities may include RTL or HDL, CAD, and robotics.

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

AI training is the human work behind systems that learn from examples, including writing evaluations and reviewing model responses. OpenTrain helps people find these projects and build a profile around their skills, while experienced specialists provide the judgment needed for demanding technical evaluations.