Monitoring and Performance Engineer

BESS Modeling Engineering e-STORAGE is a subsidiary of Canadian Solar and a leading company specializing in the design, manufacturing, and integration of battery energy storage systems for utility-scale applications. Currently, the Company operates two fully automated, state-of-the-art manufacturing facilities with an annual production capacity of approaching 20 GWh. e-STORAGE is fully equipped to continue providing high-quality, scalable energy storage solutions and contribute to the widespread adoption of clean energy. It is now one of the world\’s largest solar technology and renewable energy companies. Canadian Solar is a leading manufacturer of solar photovoltaic modules, provider of solar energy and battery storage solutions, and developer of utility-scale solar power and battery storage projects with a geographically diversified pipeline in various stages of development. Over the past 22 years, Canadian Solar has successfully delivered over 102 GW of premium-quality, solar photovoltaic modules to customers across the world. Likewise, since entering the project development business in 2010, Canadian Solar has developed, built, and connected over 9 GWp of solar power projects and over 3 GWh of battery storage projects across the world. Currently, the Company has approximately 700 MWp of solar power projects in operation, 8 GWp of projects under construction or in backlog (late-stage), and an additional 17 GWp of projects in advanced and early-stage pipeline. In addition, the Company has a total battery storage project development pipeline of 52 GWh, including approximately 2 GWh under construction or in backlog, and an additional 50 GWh at advanced and early-stage development. bankable companies in the solar and renewable energy industry. Position Title: BESS Modeling Engineering Department: Engineering Reports To: Director of Controls Engineering The BESS Modeling Engineer will play a critical role in developing, implementing, and maintaining digital twin models and AI-driven analytics for Battery Energy Storage Systems. This role focuses on creating accurate system representations to enhance performance optimization, predictive maintenance, and real-time decision-making capabilities. They will be responsible for designing, implementing, and enhancing machine learning models and AI systems to optimize industrial and energy assets. This role requires a strong foundation in simulation modeling, machine learning, and AI-driven analytics to create systems that improve operational efficiency, predict failures, and deliver actionable insights. Develop and implement machine learning models to optimize BESS performance, including charge/discharge cycles, thermal management, and lifecycle predictions. Create predictive maintenance algorithms to enhance system reliability and minimize downtime. Analyze IoT sensor data to identify anomalies and optimize BESS efficiency and safety. Collaborate with cross-functional teams to integrate machine learning solutions into BESS control and monitoring platforms. Build scalable data pipelines for processing large volumes of time-series and operational data from BESS assets. Perform rigorous testing and validation of machine learning models using historical and real-time BESS data. 3+ years of experience in machine learning development, simulation modeling, and AI/ML applications within the energy or BESS industry. ~ Demonstrated experience in predictive maintenance, optimization algorithms, and failure analysis for energy storage systems. ~ Familiarity with edge computing solutions and industrial automation frameworks specific to BESS. ~ Proven ability to work with large data sets and build scalable AI-driven systems tailored to energy applications. ~ Hands-on experience working with IoT sensors and time-series data from BESS systems. Programming: Proficiency in programming languages such as Python, C++, or R. Strong understanding of machine learning frameworks and libraries (e.g., Experience with Linux command-line. Hands-on experience with cloud-based environments such as AWS, Azure, or GCP. Knowledge of big data platforms and tools for IoT data processing and real-time analytics specific to energy storage. Programming knowledge: Scripting (Python, Batch), relationship & time series databases, writing automated tests, Jupyter, Deepnote. Experience with Azure and AWS cloud infrastructure. Bachelor’s or Master’s degree in Electrical Engineering, Mechanical Engineering, Computer Science, Data Science, or a related field with a focus on energy systems or BESS. A minimum of 3 years of hands-on experience in AI/ML, digital twin development, or simulation modeling for BESS. Excellent project management skills with a track record of successfully leading complex projects from concept to completion. Extensive experience in real-time embedded controls and cloud-based development of software for real-time and non-real-time energy technology platforms. Strong stakeholder management skills with a demonstrated ability to deliver and follow up on large-scale projects on time and within budget. Willingness to travel up to 25%, including international travel.