About the Role:
In this role, you will design challenging, realistic tasks drawn from your own practice, such as:
- A component sizing calculation with a worked solution,
- A tolerance stack up,
- A CAD assembly review with interference and clearance findings,
- A thermal or fluids analysis,
- A DFM and DFA review,
- A failure analysis report, or
- A test and validation plan
You will run them through frontier AI agents, and evaluate what comes back against a professional standard.
- You will work with realistic professional files, the kind a practitioner in your field actually handles, which you assemble yourself. Some tasks are compact, built around a handful of files; others are larger scenarios that take several days to build. In every case the goal is the same: a task a competent professional in your field would complete correctly and a frontier model currently gets wrong.
Experience Required:
Professional mechanical engineering experience preferred. Any specialty: design and product development, manufacturing, thermal, structural, automotive, aerospace, HVAC, robotics, energy, medical devices.
In progress Bachelor’s degree or higher in mechanical engineering or a related field. PE licensure is a plus but not required.
Depth in at least one of: mechanical design and CAD (geometry, clearances, tolerances, mechanisms); structures and materials (stress, deflection, fatigue, buckling, material selection, failure analysis); thermal and fluids (heat transfer, thermodynamics, HVAC, pumps and piping); dynamics and controls (vibration, kinematics, rotating machinery); manufacturing (DFM and DFA, process selection, GD&T, tolerance stack ups, cost and quality trade offs).
Fluency in the tools of your specialty: CAD (SolidWorks, Fusion 360, Onshape, Creo, NX, CATIA or Inventor), FEA or CFD, or MATLAB or Python for engineering analysis.
Strong fundamentals across mechanics of materials, dynamics, thermodynamics, heat transfer, fluid mechanics and manufacturing processes.
Meticulous: you check your own work and enjoy finding the edge case that breaks an assumption.
This is not a traditional mechanical engineering role. You will be helping build better AI by putting your knowledge to work in a structured, flexible, fully remote environment.
The work is long form and self directed, and clear written reasoning matters as much as technical depth
Process:: Assessment- 2-3 hours (unpaid)