Mechanical Engineering Assessment Writer

About OpenTrain

OpenTrain is the #1 platform for finding and building careers in AI training and data labeling. We hire and contract subject-matter experts to author, review, and improve the examples that teach modern AI systems.

Working with OpenTrain means contributing to a growing industry while building a unified portfolio of AI training work you control—no need to reconstruct proof of work across multiple places.

About AI training and this work

AI training (data labeling, annotation, or human feedback work) is the human-led side of building AI systems: people prepare, evaluate, and refine the examples models learn from. This role sits at the intersection of mechanical engineering subject-matter expertise and educational content creation.

This work is remote and asynchronous, making it a flexible, durable way to earn from technical knowledge while helping shape how engineering models perform.

The role

You will create rigorous graduate-level single-option multiple-choice assessment items, write detailed rationales and explanations, and review AI-generated mechanical engineering materials for technical accuracy and pedagogical quality.

Tasks will include authoring questions across advanced topics (Solid & Structural Mechanics, Dynamics & Vibration & Control, Thermal-Fluids), conducting quality checks, applying revisions, and collaborating asynchronously using digital workflow tools.

• Labeling types: Classification, Text Generation, Evaluation/Rating
• Employment: Contractor, Part-time
• Work location: 100% remote, worldwide

What you'll do

Focus on producing exam-quality content and validating AI outputs. Expect a mix of original question writing, writing answer rationales, and auditing or correcting AI-generated material.

• Design rigorous single-option multiple-choice questions in your specialty.
• Write clear, precise explanations and answer-choice rationales suitable for graduate exams.
• Review and validate the technical accuracy of AI-generated mechanical engineering content.
• Perform revisions, enhancements, and quality assurance on contributed work.
• Maintain organized records and communicate asynchronously with the project team.

Requirements

You must meet the stated academic and teaching prerequisites and demonstrate experience with graduate-level assessment design or grading.

• PhD or MS in Mechanical Engineering (required).
• University-level teaching experience (professor, adjunct, lecturer, or TA).
• Experience authoring, grading, or reviewing graduate-level exams, problem sets, or coursework.
• Demonstrated ability to convert complex engineering principles into clear, accurate written content.
• Strong written communication, attention to technical detail, and ability to work independently in a remote asynchronous environment.

Who should apply

This role is a fit for mechanical engineers who teach or have authored graduate coursework and who enjoy translating advanced technical concepts into assessment items and explanations.

If you want flexible remote contract work that leverages your teaching and subject-matter expertise to directly influence how engineering AI behaves, apply.

Compensation, time, and logistics

Pay is hourly on a per-contract basis. Expected commitment is approximately 20+ hours per week; the role is part-time and contractor-based.

• Rate range: $60–$130 USD per hour (typical pay up to $130/hr).
• Estimated time requirement: 20+ hours/week.
• Language: English (required).

How it works — apply and start

If you meet the requirements, applying creates an OpenTrain profile that documents your work and lets you discover similar projects over time. Selection includes review of credentials, relevant teaching or assessment samples, and a technical check of submitted items.

Work is completed asynchronously using digital workflow tools; collaboration and feedback occur via written review and revision cycles.

• You will be contracted by OpenTrain and work remotely.
• Work product includes multiple-choice questions, detailed rationales, and reviewed AI-generated content.