Lead Engineer - Digitalization & AI

Position Overview

The Digital Engineering team is currently seeking a Lead Engineer – Digitalization & AI to support AI-enabled engineering transformation initiatives across the enterprise. Eaton’s Digital Engineering is a corporate RDE function within Eaton's Corporate CTO office, responsible for innovative and breakthrough design strategy development for Eaton’s products and services. You will collaborate across divisions, CoEs, product teams, IT, and global engineering groups to architect, develop, and industrialize AI and digital engineering technologies supporting Eaton’s future products and platforms.

With focus on delivering value, the Digitalization and AI Lead Engineer will combine engineering domain expertise and AI to develop production-ready workflows spanning requirements, architecture, design, simulation, test, and manufacturing, increasing engineering throughput and product quality.

Making what matters work at Eaton takes the passion of every employee around the world. We create an environment where creativity, invention and discovery become reality, each day. It’s where bold, bright professionals like you can reach your full potential—and where you can help us reach ours.

• Create Agentic AI design models performing end‑to‑end design optimization, meshing, simulation, constraint checks, manufacturability scoring, and design iteration
• Integrate 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 Sim Ready, 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
• Deploy enterprise‑scale digital twins for design, operations, and manufacturing with connected digital threads

• Master’s or PhD in Mechanical Engineering, Electrical Engineering, Aerospace Engineering, Computer Science, Applied Mathematics, or related field
• Minimum of three (3) years developing AI/ML models, CAE workflows, or digital twin systems
• Minimum of two (2) years of industry experience in aerospace, electrical systems design, or a relevant engineering discipline
• Must be able to work in the United States without corporate sponsorship now and in the future
• Forward thinking, fast learning, and good problem‑solving skills

• Masters 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

• Forward thinking, fast learning, and excellent problem‑solving skills
• Strong written and verbal communication skills in dealing with senior management, colleagues, customers, and suppliers
• Ability to multi‑task and work in collaborative teams to achieve organizational goals
• Business and/or research acumen with a proven record of formulating value proposition

We are committed to ensuring equal employment opportunities for all job applicants and employees. Employment decisions are based upon job‑related reasons regardless of an applicant's race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, marital status, genetic information, protected veteran status, or any other status protected by law.

Eaton believes in second‑chance employment. Qualified applicants with arrest or conviction history will be considered regardless of their arrest or conviction history, consistent with the Los Angeles County Fair Chance Ordinance, the California Fair Chance Act and other local laws.

You do not need to disclose your…