Mechanical Engineering QA Lead - Remote

YO IT Consulting is a fast-growing AI Data Services company delivering training data for major AI companies. They are seeking a Mechanical Engineering Quality Assurance Lead to oversee quality and consistency in mechanical engineering AI training projects, ensuring that all contributors follow quality standards and that the engineering content is accurate and well-documented.

Responsibilities:

• Quality monitoring: Spot-check mechanical engineering items, identify quality issues, provide ongoing feedback through DMs, and escalate recurring or critical issues
• Technical review: Evaluate AI-generated engineering explanations, calculations, design recommendations, diagrams/descriptions, and problem-solving steps for correctness and clarity
• Trainer and QA communication: Update trainers and QAs on Discord about new item guidelines, project changes, workflow updates, quality expectations, and engineering-specific review standards
• Question handling: Respond to trainer/QA questions clearly and promptly, especially around engineering assumptions, units, formulas, calculations, safety concerns, standards references, and rubric interpretation
• Trainer/QA activation management: DM contributors who are inactive or not working, encourage activation, track follow-ups, and flag availability issues when needed
• Documentation: Create and maintain mechanical engineering project documentation, including style guides, trackers, FAQs, quality notes, examples, honeypots, calibration tasks, and onboarding materials
• Onboarding and training: Schedule and run onboarding/training calls with trainers and QAs to explain project expectations, workflows, rubrics, quality standards, and mechanical-engineering-specific review requirements
• Quality alignment: Ensure all trainers and QAs apply engineering guidelines consistently and understand updates as projects evolve
• Risk and safety review: Flag unsafe, misleading, or overconfident engineering recommendations, especially where design, manufacturing, equipment, structural integrity, or operational safety may be affected
• Process improvement: Identify recurring quality gaps, propose workflow improvements, and help build scalable QA processes for mechanical engineering AI training projects

Requirements:

• Bachelor's or Master's degree in Mechanical Engineering, Aerospace Engineering, Mechatronics, Manufacturing Engineering, or a closely related engineering field
• Strong grasp of the English language to follow project guidelines, communicate with teams, and provide clear technical feedback in English
• 3+ years of professional experience in mechanical engineering, product design, manufacturing, R&D, systems engineering, CAD, simulation, technical review, engineering education, or related workflows
• Strong understanding of core mechanical engineering topics such as 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 issues such as incorrect assumptions, flawed calculations, missing units, unsafe recommendations, poor reasoning, hallucinated standards, or incomplete explanations
• Comfortable working in fast-moving remote environments using tools such as Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems
• Highly detail-oriented and organized, with the ability to maintain style guides, FAQs, trackers, onboarding materials, honeypots, calibration tasks, and other quality documentation
• Familiarity with common engineering tools or workflows such as CAD, FEA/CAE, MATLAB, Python, SolidWorks, AutoCAD, ANSYS, Fusion 360, or similar tools
• Experience leading or supporting remote teams of trainers, annotators, reviewers, engineers, technical writers, or QAs
• Experience with AI training, data annotation, large language models, prompt/response evaluation, technical content QA, or rubric-based LLM evaluation