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Eaton

Power management leader for electrical systems

Lead Engineer - Engineering Digitalization & AI, Research & Development Engineering

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeUnited States$105k - $154k /yr

About the Job

Requirements

  • A Master's or PhD in Mechanical Engineering, Electrical Engineering, Aerospace Engineering, Computer Science, Applied Mathematics, or a related field is required.
  • At least three years of experience developing artificial intelligence or machine learning models, computer-aided engineering workflows, or digital twin systems is required.
  • At least two years of industry experience in aerospace, electrical systems design, or a relevant engineering discipline is required.
  • Extensive knowledge of computing, artificial intelligence, and AI agent development is required.
  • Candidates must be able to work in the United States without corporate sponsorship now or in the future.
  • Candidates must currently reside within 50 miles of a US Eaton location; relocation benefits are not offered.
  • Strong experience in product development using high-fidelity multiphysics models is preferred.
  • Expertise in artificial intelligence, physics-informed machine learning, and digital twins is preferred.
  • Experience with multiple computer-aided engineering tools, such as ANSYS, Abaqus, or MATLAB Simulink, is a plus.
  • Strong written and verbal communication skills when dealing with senior management, colleagues, customers, and suppliers are required.
  • The ability to multitask and work collaboratively to achieve organizational goals is required.
  • Business or research acumen and a proven record of formulating a value proposition are required.

Responsibilities

  • Create agentic AI design models for end-to-end design optimization, meshing, simulation, constraint checks, manufacturability scoring, and design iteration.
  • Integrate AI into traditional engineering tools for requirements management, design failure mode and effects analysis, design for six sigma, and related practices to improve engineer productivity and process efficiency.
  • Develop multiphysics digital twins and 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-simulation engines combining physics-informed neural networks, finite element solvers, and surrogate inference to automate geometric optimization loops and provide real-time design guidance.
  • Build internal computer-aided-design-aware transformer and graph neural network models trained on Eaton’s 3D portfolio to enable design retrieval, completion, and conditional regeneration.
  • Deploy enterprise-scale digital twins for design, operations, and manufacturing with connected digital threads.

Desired Qualifications

  • A Master's degree in an engineering discipline or related field from an accredited institution is preferred.

About the Company

Eaton

Power management leader for electrical systems

Eaton designs and sells electrical power management products and services for data centers, utilities, aerospace, and other industries. It provides hardware like switches, circuit breakers, transformers, and distribution equipment, plus software and services to monitor, protect, and optimize power flow from generation to end use. It combines an end-to-end power management portfolio with a long history of acquisitions to be a broad, globally integrated provider. Its goal is to enable reliable, efficient, and safe electrification across industries by improving energy management and resilience.

Company size
10,001+
Company stage
IPO
Headquarters
Dublin, Ireland
Founded
1911

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