Mechanical Engineering AI Trainer

When AI gets the details wrong in your field, real people pay for it. The people who know the work best have to be the ones training these models. You’re not being replaced by AI. You’re making sure it’s used accurately and safely.

• Design challenging, realistic mechanical engineering tasks based on professional practice, including scenarios, colleague-style prompts, and self-authored supporting files such as drawings, CAD models, load cases, material data, test data, and specifications.
• Run tasks through frontier AI models and evaluate calculations, design reviews, analyses, and reports against professional engineering standards.
• Compare model outputs generated from identical prompts and files, determine which output is stronger, and document specific strengths and shortcomings.
• Write closed-ended engineering problems with worked solutions, acceptance criteria, and detailed grading rubrics.
• Identify and document concrete errors, including incorrect boundary conditions, unit errors, missed interferences, non-closing tolerance stacks, unsafe factors of safety, fabricated or ignored source files, and misinterpretation of the brief.
• Contribute expertise across mechanical design, analysis, manufacturing, and testing, and review or refine tasks created by other engineers.
• Build professional task scenarios ranging from compact file sets to larger multi-day engineering cases.
• Incorporate expert feedback and revise task proposals, files, rubrics, and evaluations as needed.

• 2+ years of professional mechanical engineering experience preferred; candidates with less experience may be considered when they have substantial practical hands-on work.
• In-progress Bachelor's degree or higher in mechanical engineering or a related field.
• Hands-on individual-contributor experience in mechanical engineering, currently or recently, rather than solely management experience.
• Depth in at least one area: mechanical design and CAD; structures and materials; thermal and fluids; dynamics and controls; or manufacturing.
• Strong mechanical engineering fundamentals, including mechanics of materials, dynamics, thermodynamics, heat transfer, fluid mechanics, and manufacturing processes.
• Fluency with tools relevant to the specialty, such as CAD software including Solid Works, Fusion 360, Onshape, Creo, NX, CATIA, or Inventor; FEA or CFD tools; or MATLAB or Python for engineering analysis.
• Ability to create realistic scenarios from real-world workflows and assess whether AI systems can complete the work correctly.
• Full professional or native-level written and spoken English, with the ability to clearly explain complex technical reasoning and why an answer is incorrect.
• Meticulous attention to detail, including the ability to verify assumptions, numbers, source materials, and engineering conclusions.
• Comfort working independently with ambiguity, incomplete instructions, and unfamiliar file sets.
• Ability to interpret feedback critically and apply appropriate revisions without extensive supervision.
• General familiarity with AI and LLM tools such as Claude or ChatGPT, including the judgment to distinguish well-reasoned work from plausible but incorrect output.
• Comfort using cloud file tools, browser profiles, desktop applications, and routine file handling such as spreadsheet conversion and zipping files.
• Availability of at least 10 hours per week, with consistent availability preferred.
• Based in the United States, Canada, or the United Kingdom.
• PE licensure is a plus but not required.

• Pay of $40-$125 USD per hour, paid via Pay Pal on a regular cadence.
• Fully remote contract work with flexible scheduling.
• Minimum commitment of 10 hours per week, with no weekly maximum and full-time hours available.
• Multi-day task timers that allow work to be spread across several days.
• Access to Claude and ChatGPT through the project; no personal subscription required.
• Paid work for completed accepted stages of the project process, including onboarding and training work.
• Structured onboarding, platform instructions, dedicated Slack support, office hours, and written expert feedback.
• Opportunity to help improve frontier AI systems using real mechanical engineering expertise.