Eaton's CTO Corporate Technology Office division is currently seeking a Engineering Specialist, Digitalization & AI. The preference for this role is open to a hybrid work schedule out of Southfield, MI however we will consider candidates at any Eaton site within the US or remote.

The expected annual salary range for this role is $122000 - $179000 a year.

Please note the salary information shown above is a general guideline only. Salaries are based upon candidate skills, experience, and qualifications, as well as market and business considerations.

What you'll do:

Position Overview:
The Digital Engineering team is currently seeking an Engineering Specialist - 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 AI & Engineering Digitalization Specialist 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.

In this role you will:
• 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.

Qualifications:

Required (Basic) Qualifications:
• 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.

Preferred Qualifications
• 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.

Skills:

Position Criteria
• 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 know that good benefit programs are important to employees and their families. Eaton provides various Health and Welfare benefits as well as Retirement benefits, and several programs that provide for paid and unpaid time away from work. Click here for more detail: Eaton Benefits Overview. Please note that specific programs and options available to an employee may depend on eligibility factors such as geographic location, date of hire, and the applicability of collective bargaining agreements.