Mechanical Design Data Specialist

Key Responsibilities

• Act as the 'domain expert' by authoring technical requirements and annotation guidelines.
• Define the rules for how engineering intent, constraints, and design rationale should be captured for AI training.
• Audit incoming CAD (NX/Teamcenter/SolidWorks/CATIA, etc.) and CAE (Simcenter/ANSYS) data to ensure it accurately represents real-world engineering intent.
• Track and document design changes across versions to create 'diff' datasets that explain why a geometry or simulation parameter was modified.
• Use CAD/CAE scripting (e.g., NX Open, Python) to generate variations of mechanical parts and simulation runs to augment training sets.

Basic Qualifications

• BS/MS in Mechanical Engineering or Aerospace Engineering.
• 5+ years of hands-on experience with commercial CAD/PLM tools (Client NX and Teamcenter preferred).
• Strong understanding of the design-to-simulation loop (FEA/CFD, etc.).
• Proficiency in Python for automating design tasks or data manipulation.

Preferred Qualifications

• Familiarity with engineering design ontologies, knowledge representations, or structured reasoning frameworks for design rationale.
• Familiarity with Cyber-Physical Systems (CPS) and safety assurance modeling.
• Hands-on experience with structural analysis (linear/nonlinear statics, dynamics, fatigue) or fluid mechanics at a level sufficient to define engineering constraints and evaluate design feasibility.
• Experience in developing data collection protocols or annotation schemas translating complex engineering tribal knowledge into structured, machine-readable requirements.
• Experience in Data-Centric AI, specifically annotating or preparing non-text datasets (3D meshes, point clouds, or field data).
• Knowledge of Graph Neural Networks (GNNs) or geometric deep learning as applied to mesh-based engineering data.