Sr. Power Electronics Engineer - Simulation and Modeling

Enphase Energy is a global energy technology company and a leading provider of solar, battery, and electric vehicle charging products. Founded in 2006, our innovative microinverter technology revolutionized solar power, making it a safer, more reliable, and scalable energy source. Today, the Enphase Energy System enables users to make, use, save, and sell their own power. Enphase is also one of the most successful and innovative clean energy companies in the world, with more than 80 million products shipped across 160 countries.

Join our dynamic teams designing and developing next-gen energy technologies and help drive a sustainable future!

Are you passionate about combining power electronics with programming? This role offers a unique opportunity to apply strong fundamentals in converter and magnetics modeling while building high-performance simulation and optimization tools that drive next-generation power conversion design.

As a Senior Power Electronics Engineer, you’ll develop and refine Python/Num Py-based frameworks for predicting converter efficiency using state-of-the-art loss models. Your work will span FEM integrations, matrix-based winding loss models, dimensional-aware core loss algorithms, and nanosecond-level DLL-based switching loss models. You’ll also leverage these tools for parametric optimization—shaping custom magnetic cores and windings to achieve breakthrough performance.

This position is part of an advanced R&D team within the CTO Office and reports directly to the Sr. Director of Inverter Technology. You’ll collaborate with world-class experts in power electronics and software engineering, with high visibility across the organization and strong potential for growth into technical leadership or strategic product roles.

• Develop and enhance Python/Num Py-based simulation frameworks for power converter and magnetics modeling.
• Implement advanced algorithms for core loss prediction (iGSE, ML-based models) and winding loss estimation using matrix and Fourier techniques.
• Integrate FEM workflows for magnetic component analysis and automate impedance matrix generation.
• Build parametric models of cores and windings to enable geometry-driven optimization and shape refinement.
• Couple simulation tools with optimization algorithms toidentifyhigh-efficiency designs under real-world constraints.
• Validate models against experimental data and continuously improve predictive accuracy.
• Collaborate with hardware design teams to accelerate development of next-generation power conversion systems.
• Contribute to software architecture decisions, code quality standards, and documentation for internal modeling frameworks.

• Strongproficiencyin Python, with experience in scientific computing and optimization using libraries such as Num Py and Sci Py.
• Solid understanding of software development best practices, including Git version control, branching strategies, unit testing, API design, and documentation.
• Ability to write clean, maintainable, and well-structured code for modeling and simulation workflows.
• Experience coupling simulation frameworks with optimization algorithms for parametric and geometry-driven design.
• Deep knowledge of power electronics fundamentals, with hands-on experience in lab measurements and validation.
• Familiarity with magneticcomponentdesign, ferrite material properties, and core loss modeling techniques (e.g.,iGSEand ML-based approaches).
• Experience with FEM tools for electromagnetic analysis and integration into design workflows.
• Understanding of resonant converter topologies and their unique modeling challenges; direct experience is a strong plus.
• Comfortable working in a fast-paced R&D environment with evolving priorities and high technical complexity.
• Bachelor’s or Master’s degree in Electrical Engineering, Computer Engineering, or a related field;
  PhD or equivalent experience in power electronics or magnetics modeling is a plus.

The base pay range for this position is $105,000 to $162,000 per year. This salary range may be modified in the future. The successful candidate’s starting pay will be determined based on job-related skills, experience, education or training, work location, and market conditions. This position is also eligible for bonus, equity, and benefits.