Brunel is partnering with DataAnnotation to connect experienced Mechanical Engineers with an innovative AI training program. This opportunity brings together hands-on mechanical engineering expertise and artificial intelligence to help evaluate and improve how AI models solve real-world engineering problems. Selected experts will contribute their knowledge to the development of high-quality, technically accurate AI systems.
This opportunity is designed for practicing engineers across mechanical design and CAD, structures and materials, thermal and fluid systems, dynamics and controls, manufacturing, automotive, aerospace, HVAC, robotics, energy, and related mechanical engineering disciplines.
The models can already communicate fluently about mechanical engineering concepts. The challenge is teaching them to reliably perform the actual engineering work: sizing components against real load cases, identifying potential failure modes, evaluating CAD assemblies and clearances, analyzing design changes, and understanding downstream impacts. Your engineering judgment will help establish the benchmark against which these AI models are evaluated.
Engagement Details
Engagement
Fully remote, project-based work with a flexible schedule. Around 10 hours per week is the recommended starting point; the project prioritizes engineers who can commit 30–40 hours per week, though part-time availability is considered.
Pay Rate
$40–$125+ USD/hour, paid via PayPal
Location
United States, Canada, United Kingdom, Ireland, Australia, and New Zealand
First Step
Skills assessment (1–3 hours)
Responsibilities:
- Design challenging, closed-ended mechanical engineering problems based on your own professional experience that require genuine engineering reasoning rather than simple information lookup.
- Derive and verify the correct answers to your problems and develop clear, technically rigorous worked solutions demonstrating your methodology.
- Test engineering problems against advanced AI models and refine them to appropriately challenge the models’ reasoning capabilities.
- Evaluate AI-generated mechanical engineering analysis, designs, calculations, and technical documentation for accuracy and real-world applicability.
- Compare AI-generated solutions and determine which performs better, identifying specific strengths, weaknesses, and technical errors.
- Identify and document concrete failures, including incorrect assumptions, calculation or unit errors, unrealistic results, overlooked failure modes, improper material or component selection, and misinterpretation of engineering requirements.
- Review problems and solutions developed by other engineering contributors for technical correctness, ambiguity, rigor, and practical relevance.
- Apply your expertise across one or more mechanical engineering disciplines, including:
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Mechanical Design & CAD: geometry, clearances, tolerances, mechanisms, assemblies, and the impact of design changes.
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Structures & Materials: stress, deflection, fatigue, buckling, material selection, and failure analysis.
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Thermal & Fluids: heat transfer, thermodynamics, HVAC, pumps, piping, and fluid mechanics.
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Dynamics & Controls: vibration, kinematics, rotating machinery, and control systems.
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Manufacturing: DFM/DFA, process selection, GD&T, tolerance stack-ups, and cost and quality trade-offs.
Qualifications:
- Fluency in English, with the ability to communicate complex technical reasoning clearly in writing.
- 2+ years of professional mechanical engineering experience in design, product development, manufacturing, thermal systems, structural engineering, automotive, aerospace, HVAC, robotics, energy, or a related discipline.
- Background in Mechanical Engineering or a closely related engineering field.
- Strong engineering fundamentals, including knowledge of mechanics of materials, dynamics, thermodynamics, heat transfer, fluid mechanics, and manufacturing processes.
- Experience with tools relevant to your engineering specialty, which may include CAD platforms such as SolidWorks, Fusion 360, Onshape, Creo, NX, CATIA, or Inventor; FEA/CFD tools; or MATLAB/Python for engineering analysis.
- Ability to develop precise, technically rigorous, and unambiguous engineering problems and clearly explain the reasoning behind the correct solution.
- Ability to articulate why an engineering answer or design is incorrect, not simply identify that it is wrong.
- Strong attention to detail and the ability to identify edge cases, incorrect assumptions, and potential failure modes.
- Working comfort with AI tools, or the ability to learn and use them quickly.
- A current, in-progress, or completed Bachelor’s degree in Mechanical Engineering or a related field.
Relevant Backgrounds:
This opportunity may be particularly relevant for professionals currently working as:
- Mechanical Engineer
- Mechanical Design Engineer
- Product Engineer
- Manufacturing Engineer
- Structural/Mechanical Engineer
- Thermal Engineer
- HVAC Engineer
- Automotive Engineer
- Aerospace Engineer
- Robotics Engineer
- Mechanical Systems Engineer
Note: Payment is made via PayPal. We will never ask for any money from you. PayPal will handle any currency conversions from USD. Only applicants based in Australia, Canada, Ireland, New Zealand, the United Kingdom, and the United States will be considered for this role.
This is an independent contractor position.
#RPOCAD
Originally posted on Himalayas