You will turn complex physical engineering challenges—spanning conceptual 3D parametric CAD, CAE simulation (FEA, CFD), DFM/DFA, and physical testing—into structured test problems, define physical grading criteria, and diagnose why frontier AI models succeed or fail.

Contract Start Date: Expected between 20 october - 23 october.

Engagement: 8 weeks (with potential chances of extension).

Engagement Type: Contract.

• Convert real-world mechanical engineering challenges into structured test scenarios with defined inputs, requirements, kinematic/geometric constraints, and verified golden reference solutions.
• Design clear scoring rubrics & programmatic validation rules for automated task verification by software engineers (e.g., verifying stress concentrations, mesh convergence, boundary conditions, tolerance stacks, GD&T adherence).
• Assess the behavior of state-of-the-art AI agents to diagnose & analyse failure modes.
• Design and manage automated and human-expert-in-the-loop QA/QC workflows to ensure dataset quality.
• Recruit and coordinate teams of internal and external engineers to build and scale training and evaluation datasets.

• Experience: 15+ YOE in the field.
• Bachelor’s or Master’s degree in Mechanical Engineering, Aerospace Engineering, Automotive Engineering, or a closely related physical discipline.
• 15+ years of industry track record delivering hardware from concept to production in top-tier automotive, aerospace, or advanced precision engineering environments.

Work arrangement: Fully remote