AI Trainer Mechanical Engineers

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
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 3040 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 (13 hours)

• 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:
• Mechanical Design & CAD: geometry clearances tolerances mechanisms assemblies and the impact of design changes.
• Structures & Materials: stress deflection fatigue buckling material selection and failure analysis.
• Thermal & Fluids: heat transfer thermodynamics HVAC pumps piping and fluid mechanics.
• Dynamics & Controls: vibration kinematics rotating machinery and control systems.
• Manufacturing: DFM/DFA process selection GD&T tolerance stack-ups and cost and quality trade-offs.

• 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 Bachelors degree in Mechanical Engineering or a related field.

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.