About the job
At Sunlight Group, we are at the forefront of revolutionizing energy storage solutions for industrial and advanced technology applications. Our commitment to performance and continuous improvement drives us to create innovative solutions that not only meet client needs but also contribute to a sustainable future. With a strong emphasis on environmental responsibility, we champion a culture of openness and respect in all interactions. Our customer-centric approach leverages data and insights to empower our clients and enhance our shared ecosystem. We embrace an entrepreneurial spirit, fostering an agile and collaborative environment that inspires our team through open communication, continuous learning, and opportunities for personal growth.
Our Vision: Transforming Energy Storage Solutions to Power a Sustainable Tomorrow.
Our Mission: We deliver cutting-edge, high-quality energy storage solutions for industrial and advanced technology applications, driving an all-electric future.
We are seeking an AI Energy Systems Engineer to join our R&D Smart Energy Systems team. This role integrates artificial intelligence, energy management, and applied engineering to design and implement AI-driven solutions that optimize energy storage, distribution, and grid interaction across industrial, commercial, and renewable energy systems. As part of our team, you will contribute directly to the advancement of clean energy systems, collaborating with like-minded professionals dedicated to pioneering intelligent and sustainable infrastructure.
Key Responsibilities:
- Design and deploy AI/ML models, including neural networks for load forecasting, energy storage optimization, anomaly detection in grid operations, predictive maintenance, and fault classification.
- Integrate machine learning pipelines into operational Energy Management Systems (EMS) and SCADA architectures.
- Develop and simulate electrical power system models and apply reinforcement learning or optimization algorithms to dynamic energy challenges.
- Create robust data pipelines and preprocessing frameworks for training on large datasets.

