Green Fusion

Machine Learning Engineer

• Support our Sector Coupling team building the next generation of intelligent Energy Management Systems (EMS).
• Enable high-accuracy model predictions and optimizations through long-term learning from our data to save energy every single day.
• Design and improve machine learning models for time-series forecasting and nonlinear optimization, taking them from concept to deployment.
• Bring forecasting and optimization models into our EMS production environment (Cloud and Edge).
• Maintain and improve ML pipelines (using tools like Prefect and MLFlow) to support the full model lifecycle—from experiment tracking to training and validation.
• Act as the guardian of our data, ensuring feature engineering for time-series, asset telemetry, and market data is robust.
• Lead the monitoring of model quality, handling concept drift and performance evaluation.
• Lead the development of digital twins and simulation environments to safely test how our EMS interacts with components before they touch real hardware.
• Collaborate with embedded and platform teams to integrate your work into the GreenBox edge device and backend services.