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Mechanical Engineer Quality Assurance Lead (QAL)

SME Careers • Remote, open in United States

Education

Master's

Type

Hourly

Pay

Up to $75/hr

The most this role pays. Your rate depends on your skills and experience.

Last checked

Today

Checked

Only apply if this role fits your skills and interests.

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What we know about this role

Interview
Required i As stated in the listing: “Selection process involves an AI interview, a domain-specific task, and an interview with a recruiter.”

About this role

From the SME Careers listing

In this hourly, remote contractor role, you will work as a Mechanical Engineering Quality Assurance Lead (QAL) to oversee quality, consistency, and trainer performance across mechanical engineering AI training projects. You will review AI-generated mechanical engineering content and trainer/QA work, evaluate output quality against project guidelines, provide precise written feedback, and ensure that all contributors follow the expected quality standards.

You will assess work for technical accuracy, engineering reasoning, calculation correctness, standards awareness, clarity, safety considerations, unit consistency, formatting, instruction-following, and adherence to project-specific rubrics. You will spot recurring quality issues, communicate updates to trainers and QAs, support onboarding, maintain documentation, and help activate contributors who are not working consistently. This role requires strong mechanical engineering expertise, strong English communication skills, excellent attention to detail, structured communication, and the ability to manage quality workflows across remote technical teams.

This role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, delivering training data for many of the world’s largest AI companies and foundation-model labs. Your mechanical engineering quality leadership will directly help improve the world’s premier AI models by ensuring that engineering training data is accurate, logically sound, clearly explained, well-documented, and aligned with client expectations.

Selection process involves an AI interview, a domain-specific task, and an interview with a recruiter.

Important: There is no immediate project for this role; however, if qualified, you will be among the first experts we reach out to when relevant opportunities arise. This will also provide you with access to future projects available through our expert network.

Key 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.

Your profile

  • 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.
  • Familiarity with common engineering tools or workflows such as CAD, FEA/CAE, MATLAB, Python, SolidWorks, AutoCAD, ANSYS, Fusion 360, or similar tools is preferred.
  • Experience leading or supporting remote teams of trainers, annotators, reviewers, engineers, technical writers, or QAs is strongly preferred.
  • 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.
  • Experience with AI training, data annotation, large language models, prompt/response evaluation, technical content QA, or rubric-based LLM evaluation is a strong plus.

🌍 Geographic Availability This role is available to qualified experts globally. However, as a U.S.-based company, SME Careers complies with U.S. export control and sanctions regulations. Eligibility depends on your country of residence and any applicable trade restrictions. Some projects may have additional language or region-specific requirements.

💰 Pay Rate May Vary Based on Your Location Your actual compensation will be determined based on your location and local market conditions. See regional job listings for localized pay information, or the application process will clarify your specific rate.

If you're unsure whether you're eligible, proceed with the application—SME's screening will determine your jurisdiction status and applicable compensation.

How long hiring takes

On the platforms we refer people to, half of hires came within about 25 days of applying. Time from applying to hire:

Under 2 weeks
~30%
2 weeks to 6 weeks
~40%
6 weeks to 3 months
~15%
Over 3 months
~15%

Why this role

This Mechanical Engineering QAL role pays $75/hr to oversee quality across mechanical engineering AI training projects. A degree in mechanical, aerospace, or mechatronics engineering is required, along with three or more years of product design, manufacturing, or R&D experience. Someone who has spent years signing off on other engineers' calculations will find that same review instinct is what this role is built around.

Talent pool

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Common questions

How does SME Careers pay freelancers?

Weekly, through Deel. Deel also handles tax paperwork, which lets SME Careers pay contractors in more than 40 countries.

Is SME Careers work ongoing or project-based?

It's project-based, and how long projects last varies. Good work gets you first pick of the next project.

Is research-level AI training steady work?

Usually not. Work comes in projects, such as training a model on quantum mechanics, that can last a few weeks. Plan for it like a short fellowship.

Is research-level AI training the same as data labeling?

It's closer to academic research. You write or check proofs, solve advanced problems and test the logic behind a model's step-by-step reasoning in your field.

What does STEM work look like for a Mechanical Engineer Quality Assurance Lead (QAL)?

You check AI answers to STEM questions, correct their errors and write expert reasoning. As a Mechanical Engineer Quality Assurance Lead (QAL), you're hired for that judgment, so hands-on STEM experience matters.

What specific skills does this listing call for?

Mechanical Engineering, Engineering Calculations, LLM Evaluation, and Design Review are named directly in the listing. If you don't have hands-on experience with these, expect the screening to test for them.

How much does this specific role pay?

This listing is posted at up to $75/hr, an hourly rate. Pay can change after we check the listing, so confirm the rate on the platform's application page.

What happens when I click Apply on this listing?

Apply opens SME Careers' site, where you create an account and follow its sign-up steps.

Do I need a Master's to qualify?

This role lists a master's degree. The domain assessment usually matters more, and if you pass it the degree is often secondary. Some platforms check credentials, so list your qualifications accurately.

Is there an interview?

Yes. Selection process involves an AI interview, a domain-specific task, and an interview with a recruiter.

Who is behind SME Careers?

SME Careers is the expert hiring arm of SuperAnnotate, an AI data company. It hires domain experts for AI training projects.