Lead Engineer- Advanced Computational Methods for Power Systems

Eaton Corporation•Menomonee Falls, WI

34d•Remote

About The Position

Eaton’s CTO Corporate Technology Office division is currently seeking a Lead Engineer- Advanced Computational Methods for Power Systems. This position will be remote. The ERL is a corporate R&D function within Eaton's Chief Technology Office, responsible for innovative and breakthrough technology development and commercialization for Eaton products and service solutions. This position will lead the R&D of advanced computing techniques to enhance energy resilience for the electric grid and connected energy systems. The Lead Engineer will report to Technology Manager and help identify key technical gaps and influence technology roadmap for Eaton’s products and services. This work will help businesses across Eaton solve critical business problems and uncover new business opportunities.

Requirements

PhD degree or PhD candidate within 6 months to graduation in Electrical Engineering, Computer Science, or related field from an accredited institution, OR Master’s degree in Electrical Engineering, Computer Science, or related field from an accredited institution plus 3 years of industrial experience, OR Bachelor’s degree in Electrical Engineering, Computer Science, or related field from an accredited institution plus 5 years of industrial experience.
Candidates should have experience in advanced computational methods for power systems including quantum-inspired algorithms and/or high-performance computing (HPC).
Proficiency in Python and MATLAB for algorithm development is essential, along with familiarity with machine learning frameworks such as PyTorch or TensorFlow.
Eaton will not consider applicants for employment immigration sponsorship or support for this position. This means that Eaton will not support any CPT, OPT, or STEM OPT plans, F-1 to H-1B, H-1B cap registration, O-1, E-3, TN status, I-485 job portability, etc.

Nice To Haves

Ideal candidates will bring experience with quantum computing concepts, including quantum-inspired algorithms, quantum error correction (QEC) codes and hybrid algorithm strategies, or demonstrate some backgrounds and a strong willingness to learn these areas.
Practical knowledge of quantum error mitigation (QEM) techniques and hybrid simulation workflows is highly valued.
Experience with cloud platforms, preferably Google Cloud, for scalable compute and containerization tools like Docker or Kubernetes is required.
Familiarity with quantum hardware platforms such as IBM Heron or Infleqtion Sqale is a plus, as is exposure to combinatorial optimization problems on such platforms.
Knowledge of containerization and CI/CD practices for cloud-based workflows will be advantageous.
Additional strengths include experience with real-time simulations, hardware-in-the-loop platforms, and advanced numerical methods for energy systems.
Candidates who are adaptable, eager to learn emerging technologies, and capable of bridging theory with practical implementation will thrive in this role.

Responsibilities

Serve as a technical contributor and/or lead in technology development and demonstration.
Serve as an individual contributor and subject matter expert in government and non-government proposal development and/or project execution related to all aspects of advanced computation environment.
Lead development of advanced computational methods to improve energy resilience and support the transition to sustainable power systems.
Design and integrate quantum-inspired algorithms for energy systems applications like contingency analysis, leveraging cloud-based workflows and partner quantum platforms.
Build and deploy machine learning solutions to enhance reliability and reduce errors in emerging quantum technologies.
Collaborate with internal teams and external partners to validate solutions across diverse hardware and cloud environments.
Define and track performance metrics to ensure solutions meet technical and operational goals.
Investigate, integrate, and validate new product designs abiding by time-based milestones. Engage multiple business stakeholders, cross-functional teams, National labs, Universities, and Customers.
Innovate, invent, and challenge state-of-art design & process by securing critical intellectual properties through patents and publications in reputable peer-reviewed journals.