Key skills
AI/ML model developmentCAE workflowsDigital twin systemsMulti-physics modelingArtificial intelligencePhysics-informed machine learningANSYSAbaqusMATLAB SimulinkMechanical EngineeringElectrical EngineeringAerospace EngineeringApplied MathematicsComputer ScienceMATLABAIArtificial IntelligenceMachine LearningMLAgenticCollaboration
About this role
Eaton is a global technology leader in power management and they are seeking an Engineering Specialist in Digitalization & AI. This role focuses on supporting AI-enabled engineering transformation initiatives and involves collaboration across divisions to develop and industrialize AI and digital engineering technologies.
Responsibilities:
- Create Agentic AI design models performing end‑to‑end design optimization, meshing, simulation, constraint checks, manufacturability scoring, and design iteration
- Integrating AI into traditional engineering tools for RM, DFMEA, DFSS, etc. to enhance engineers productivity and process efficiency
- Develop Multi‑physics digital twins. Drive cross‑domain model integration for electromagnetics, thermal, structural, fluid, and control systems, aligned with NVIDIA Omniverse SimReady, and similar initiatives
- Build Physics AI co‑sim engines combining PINNs + FE solvers + surrogate inference to automate geometric optimization loops and real‑time design guidance
- Build internal CAD‑aware transformer/GNN models trained on Eaton’s entire 3D portfolio to enable design retrieval, completion, and conditional regeneration
- Deploying enterprise‑scale digital twins for design, operations, and manufacturing with connected digital threads
Requirements:
- Master's or PhD in Mechanical Engineering, Electrical Engineering, Aerospace Engineering, Computer Science, Applied Mathematics, or related field
- Minimum of five (5) years developing AI/ML models, CAE workflows, or digital twin systems
- Minimum of three (3) years of industry experience in aerospace, electrical systems design, or relevant engineering discipline
- Must be able to work in the United States without corporate sponsorship now and in the future
- PhD in an engineering discipline or related field from an accredited institution
- Demonstrated strong experience in product development using high fidelity multi-physics models
- Expertise in artificial intelligence, physics-informed machine learning, and digital twins
- Experience in multiple CAE tools including ANSYS, Abaqus, MATLAB Simulink, or similar software applications is a plus