Staff Engineer Simulation, Optimization and AI

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!

About the Role

We are looking for a Staff Engineer with deep expertise in simulation, optimization, and AI-driven forecasting to lead the development of advanced simulation frameworks and products for Home Energy Management Systems (HEMS). This role is central to our mission of enabling intelligent, cost-effective, and sustainable energy use in residential homes.

You will design and implement scalable simulation models that integrate photovoltaics (PV), battery storage, HVAC, heat pumps, EVSE, and other residential energy assets, and couple them with optimization solvers and machine learning-based forecasting algorithms to optimize energy bills of a homeowner. Your work will directly support product innovation, cost-benefit analysis, and strategic decision-making.

Key Responsibilities:

• PV systems, battery storage, HVAC, heat pumps, water heaters, EVSE, and grid interactions.

Key Qualifications:

 Bachelor’s or master’s degree in Electrical Engineering, Mechanical Engineering, Energy Systems, Computer Science, or a related field.

 7+ years of experience in energy systems modeling, simulation, or optimization.

 Strong experience with:

• Modeling of residential energy devices (PV, battery, HVAC, EVSE, etc.)
• Hands on experience of modelling simulation tools for home energy management
• Formulating and solving Mixed Integer Linear Programming (MILP) problems.

• Proficiency in Python and relevant libraries (e.g., Pyomo, Pandas, NumPy, Scikit-learn).
• Experience with simulation tools such as Energy Plus or any other open-source tools
• Proven ability to design and deliver scalable, production-grade software.