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. 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.
For additional information about e-STORAGE, visit www.csestorage.com
Canadian Solar was founded in 2001 in Canada and has been listed on NASDAQ since 2006. 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. Canadian Solar is one of the most
bankable companies in the solar and renewable energy industry.
For additional information about Canadian Solar, visitwww.canadiansolar.com
Position Title:BESS Modeling Engineering
Department:Engineering
Entity:CS e-Storage
Reports To:Director of Controls Engineering
Location:UK
Position Summary:
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.
- Programming knowledge: Scripting (Python, Batch), relationship & time series databases, writing automated tests, Jupyter, Deepnote.
- Experience with Azure and AWS cloud infrastructure.
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.
