Mechanical Engineer Quality Assurance Lead (QAL)

As a Mechanical Engineer Quality Assurance Lead, you will review AI-generated mechanical engineering content and trainer quality assurance work. Your reviews will help identify technical errors, unclear reasoning, unsafe recommendations, and failures to follow project standards.

• Review mechanical engineering explanations, calculations, design recommendations, diagrams, and problem-solving steps.
• Evaluate trainer and QA work against project guidelines and detailed project rubrics.
• Check technical accuracy, calculation correctness, reasoning, safety, unit consistency, formatting, standards awareness, and instruction-following.
• Write clear feedback that explains flawed calculations, missing units, unsafe recommendations, poor reasoning, or incomplete explanations.
• Communicate workflow updates, quality expectations, and review standards to trainers and quality reviewers.
• Support onboarding, maintain project documentation, and improve quality processes for mechanical engineering AI training projects.
• Flag unsafe, misleading, or overconfident engineering recommendations when safety may be affected.

This is a part-time contract role for candidates in the United States. The work requires professional mechanical engineering experience and strong English communication for detailed technical feedback and team coordination.

• $75 per hour.
• 20+ hours per week.
• Open to candidates in the United States.
• Part-time contractor position.
• Degree in Mechanical Engineering, Aerospace Engineering, Mechatronics, Manufacturing Engineering, or a closely related field.
• At least 3 years of professional experience in mechanical engineering, product design, manufacturing, research and development, systems engineering, CAD, simulation, technical review, or engineering education.
• Strong understanding of mechanics, thermodynamics, fluid mechanics, heat transfer, machine design, materials, manufacturing processes, dynamics, statics, and engineering drawing interpretation.
• Ability to evaluate engineering content against detailed rubrics and identify technical, safety, reasoning, and completeness issues.
• Preferred familiarity with CAD, FEA or CAE, MATLAB, Python, SolidWorks, AutoCAD, ANSYS, Fusion 360, or similar tools.
• Experience with AI training, data annotation, prompt or response evaluation, technical content QA, or rubric-based language model evaluation is a plus.
• Helpful experience includes leading or supporting remote teams of trainers, annotators, reviewers, technical writers, or QAs.
• Comfort with remote work tools such as Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems.

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 reviewing model answers, checking technical reasoning, and rating responses against clear standards. People with subject-matter expertise are needed to catch mistakes and help make AI outputs more accurate, useful, and safe, while OpenTrain helps people find these roles and start their applications.