BESS Modelling Engineer

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. The Company offers its own proprietary LFP battery solution, comprehensive EPC services, and innovative solutions aimed at improving grid operations, integrating clean energy, and contributing to a sustainable future. e-STORAGE has successfully implemented over 3.3 GWh DC of battery energy storage solutions in various locations, including the United States, Canada, the United Kingdom, and China. This significant accomplishment solidifies e-STORAGE's position as a key player in the global energy storage integration industry.

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.

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. The ideal candidate will have a strong background in modeling, AI/ML algorithms, control systems, and energy applications. 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.

Key Responsibilities:

• 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.
• Document technical processes, methodologies, and results to ensure transparency and reproducibility.

Related Experience:

• 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.
• Experience with simulation tools (e.g., MATLAB/Simulink, Modelica, Ansys, or equivalent platforms) for modeling BESS components.
• Strong understanding of machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
• Experience with Linux command-line.

Cloud Platforms:

• 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.

Personal Qualifications:

• 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.
• Certification in AI/ML or energy storage systems is a plus.
• Excellent project management skills with a track record of successfully leading complex projects from concept to completion.
• Strong problem-solving and decision-making abilities.
• 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.
• Excellent communication and interpersonal skills, with the ability to collaborate effectively with cross-functional teams and communicate technical concepts to non-technical stakeholders.
• Willingness to travel up to 25%, including international travel.