Mechanical Engineering Quality Assurance Lead

About OpenTrain

OpenTrain is the #1 platform for people building careers in AI training and data labeling. We help contributors find specialized, remote projects, consolidate opportunities, and build a unified portfolio so they can grow durable freelance careers teaching AI. Creating an OpenTrain account is free.

About AI training and this work

AI training (also called data labeling or human feedback) is the human work that teaches AI systems to reason and behave. Mechanical engineering QA contributors review and correct model outputs so technical recommendations, calculations, and explanations are safe, accurate, and usable.

This work is often remote and flexible, and it offers an opportunity to influence how cutting-edge models handle engineering topics. Projects range from evaluating individual responses to auditing trainer/annotator work against detailed rubrics.

• Remote, flexible, part-time opportunities that fit around your schedule.
• Work directly shapes how AI systems handle engineering content and safety.

The role at a glance

OpenTrain AI is hiring a Mechanical Engineering Quality Assurance Lead to review AI-generated mechanical engineering content and trainer QA output for technical accuracy, calculation correctness, clarity, safety, units, formatting, and rubric adherence. You will give precise written feedback, maintain documentation, support onboarding, and help keep quality consistent across remote technical teams.

• Rate: $75 USD per hour.
• Time: 20+ hours per week (part-time contractor).
• Location: US-based applicants only; English required.
• Work type: Contractor, part-time; data type: text; label types: EVALUATION_RATING and RLHF.

What you'll do

• Review AI-generated explanations, calculations, design recommendations, diagrams, and step-by-step solutions for correctness and clarity.
• Evaluate trainer and QA work against project guidelines and project-specific rubrics.
• Provide clear, written technical feedback on accuracy, reasoning, unit consistency, formatting, and instruction-following.
• Communicate workflow updates, expectations, and review standards to trainers and QAs.
• Support onboarding of new contributors, maintain and update project documentation, and help improve QA processes.
• Flag unsafe, misleading, or overconfident engineering recommendations where safety could be affected, and recommend corrective actions.

Requirements

• Degree in Mechanical Engineering, Aerospace Engineering, Mechatronics, Manufacturing Engineering, or a closely related field.
• Minimum 3 years professional experience in mechanical engineering, product design, manufacturing, R&D, systems engineering, CAD, simulation, technical review, or engineering education.
• Strong knowledge across mechanics, thermodynamics, fluid mechanics, heat transfer, machine design, materials, manufacturing processes, dynamics, statics, and engineering drawing interpretation.
• Excellent written English communication skills for detailed, precise technical feedback.
• Ability to evaluate engineering content against detailed rubrics and identify flawed calculations, missing units, unsafe recommendations, poor reasoning, or incomplete explanations.
• Preferred: familiarity with CAD, FEA/CAE, MATLAB, Python, SolidWorks, AutoCAD, ANSYS, Fusion 360, or similar tools.
• AI training, annotation, rubric-based LLM evaluation, or technical QA experience is a plus.

Who should apply

This role is for experienced mechanical engineers who enjoy reviewing and improving technical content and who can communicate detailed feedback clearly. Ideal candidates have led or supported remote teams of trainers, annotators, or reviewers and are comfortable working in fast-moving remote environments.

• People with hands-on engineering experience who care about safety, units, and calculation rigor.
• Contributors who have worked with remote collaboration tools and lightweight project trackers.

How hiring and work coordination works

OpenTrain AI will hire and contract for this role. You’ll apply via your OpenTrain account, and selected contributors will be onboarded to project-specific guidelines and rubrics. Work is coordinated remotely; contributors typically use tools such as Google Sheets, Google Docs, Discord, and project trackers to receive tasks and submit reviews.

We do not require prior platform experience, but you must meet the listed technical requirements. Compensation, hours, and contractor terms will be outlined in the contract after selection.