Apply on Employer Site

Eaton · 10 hours ago

Lead Engineer - Advanced Computational Methods for Power Systems

Golden, CO

Full-time

Onsite

Senior Level, Lead/Staff

$100K/yr - $146K/yr

5+ years exp

Eaton is a global technology leader in power management solutions, and they are seeking a Lead Engineer to develop advanced computational methods for power systems. The role involves leading R&D efforts to enhance energy resilience through innovative technologies, including quantum-inspired algorithms and machine learning solutions.

Electric Vehicle

No H1B

Hiring Manager

Lesya Drigailo

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

Qualification

Advanced computational methodsQuantum-inspired algorithmsMachine learningPythonMATLABHigh-performance computingCloud platformsQuantum error correctionContainerization toolsCoachingDiversity cultureBusiness acumenCollaborationSelf-motivationCommunication skillsLeadership

Required

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

No relocation is offered for this position. All candidates must currently reside within 50 miles of Golden, CO to be considered. Active-Duty Military Service member candidates are exempt from the geographical area limitation

Preferred

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