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Job Details

MBD Chief Architect - Advanced Control Systems, AI, Machine Learning


Systems Architect


Raleigh, North Carolina, United States

Eaton’s $10B Revenue Electrical Sector - Americas (ES-A) seeks a Model-Based Design (MBD) Chief Architect. This Chief Architect will help ES-A to innovate and drive substantial transformation in MBD, with a specialized focus in Advanced Control Systems, Machine Learning (ML), and Artificial Intelligence (AI). This Chief Architect will work with the ES-A Divisions and the global sector. This role is a hybrid position, and the preferred locations are our Electrical Sector hubs in Moon Township, PA (Pittsburgh) or Raleigh, NC. Relocation assistance is available to one of these locations. Our other sites in Wisconsin (Franksville, Milwaukee, or Waukesha), Atlanta, GA, Southfield, MI, or Chicago, IL could also be considered. Up to 30% travel is expected.

What you’ll do:

As Chief Architect, you will be an integral member of an interdisciplinary Model-Based Design product development team. In this position, you will support the different divisions of the Electrical Sector Americas to drive complex and innovative control systems design, from architecture down to detailed implementation. You will partner with Firmware, Hardware, Software, and Systems architects, along with other groups to define the best strategy to implement complex and innovative logics and sensing into our products. In addition, you will lead the successful transfer of technologies coming from our research partners (ex. CIP-Center for Intelligent Power, Eaton Research Labs, and others), and other strategic external partnerships to our divisions. We expect this position to own MBD process for industrialization of MBD Control artifacts involving advanced controls and ML / AI Based algorithms.

Essential Functions

  • Model-Based Design Framework for Advanced Control Systems, ML / AI based Algorithms: Establish best-in-class MBD frameworks, including Architecture, Design, Testing, Code generation and Integration with FW / SW.
  • Educate / mentor engineers and leaders across the organization around Advanced Control Systems, ML / AI technologies and MBD, to create a culture shift that allows capability growth, standardization, and organization engagement.
  • In collaboration with other Architects and engineering leaders in ES-A Divisions, this person will be also responsible for short and mid/long term roadmaps on Model Based Design for advanced control systems, ML / AI based algorithms, covering areas like toolset standardization, Architecture, Development and Testing processes, code-generation, and solution industrialization.
  • Hands-on engagement on different projects across ES-A Divisions with MBD (Control Systems Architecture and Design, Code-Gen, FW Integration, etc.) collaborating with other MBD Architects (taking the role as a project individual contributor when necessary).
  • Serves as a Subject Matter Expert Advanced Control Systems, ML/AI Algorithms with Model-Based Design, driving the competence strategy and execution for Eaton Electrical Sector America in all required forums (external to Eaton, other Eaton groups, across ES/A divisions).


Basic Qualifications:

  • Bachelor’s degree from an accredited institution.
  • Minimum of 10 years of professional experience.
  • Minimum 7 years of experience with Complex Control Systems Architecture Design, including interfaces with Firmware and Hardware.
  • Subject Matter Expertise in Model-Based Design applied to Control Systems, including leadership on educating, collaborating, and influencing organizations to adopt and engage with Model-Based Design within a multinational organization.
  • Subject Matter Expertise around Machine Learning and Artificial Intelligence in engineering and Control Systems applications.
  • Must be able to work in the United States without corporate sponsorship now and in the future.
  • Ability to travel around 30% of the time, supporting the different divisions within ES/A.

Preferred Qualifications:

  • Master’s degree or specialization in Control Systems preferred.
  • Experience with system modeling languages to represent architectures like SysML is a plus.
  • Ability to work in a heavily matrix environment, and with the involvement of several stakeholders and process partners, requiring strong leadership, negotiation, and system level mindset.
  • Experience working with a Global and Decentralized organization.


  • Machine Learning and Artificial Intelligence based algorithms with Model-Based Design: full proficiency on developing advanced algorithms and estimators based on Machine Learning and Artificial intelligence with MBD as, for instance, Neural Networks, Reinforcement and Deep Learning. Application experience should include use cases like Predictive Maintenance, Adaptive Control, Fault Detection, System Identification, Performance Optimization, etc.
  • Control Systems Theoretical Knowledge: SISO / MIMO systems, covering a wide range of control design techniques (ex. PID, Parameter Estimation, Kalman filter, Model Predictive Control, Fuzzy logic, etc.)
  • Control Systems Model-Based Design: proficient in complex controls modeling with tools like Simulink / Stateflow, and code-generation, testing and integration with embedded Firmware (C/C++ with floating and fixed-point implementations).
  • Control Systems Architecture: Demonstrated experience with Complex Control System Architectures (involving interconnection with HW and SW elements), ideally using System Model languages like SysML.
  • Requirement definition and decomposition from the system down to the individual control components.
  • Requirements Management at system and subsystem levels with tools like DNG, Jama is a plus.
  • Model and Software Simulation: Experience with controls simulation, integration of Model-Based Controls with Plant Models for co-simulation. Experience with C-code integration with Simulink (ex. Using S-functions), allowing simulation of integrated Firmware structures (Auto-code + handwritten code).
  • Experience with languages like Python (TensorFlow, PyTorch), R, etc.
  • Familiar with several of the SW/FW development tools such as Confluence, Jira, GitHub.
  • Recognized Subject Matter Expertise in Advanced Control Systems, Machine Learning and AI based algorithms using Model-Based Design.
  • Strong project leadership, planning and communication skills and experience.
  • Excellent Analytical and problem-solving skills.

At Eaton, we strive to provide compensation and benefits that attract, engage, and retain the best talent. This includes competitive pay and a variety of benefit programs for eligible employees. The expected annual salary range for this role is $142499.97 - $208999.96 a year. This role is also eligible for a variable incentive program. 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.

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 considers qualified applicants regardless of criminal histories, consistent with local laws. To request a disability-related reasonable accommodation to assist you in your job search, application or interview process, please call us at 1-[Register to View] to discuss your specific need. Only accommodation requests will be accepted by this phone number.

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.