Digitalization and energy transition in one sentence? That’s what we do at Green Fusion! Our software holistically optimizes energy systems in the real estate sector, helping to combat climate change through digitalization and automation. We reduce emissions and energy consumption, actively advancing the energy transition. As an ML Engineer, you’ll support our Sector Coupling team building the next generation of intelligent Energy Management Systems (EMS). You will enable high-accuracy model predictions and optimizations through long-term learning from our data to save energy every single day. You will design and improve machine learning models for time-series forecasting and nonlinear optimization, taking them from concept to deployment. Working alongside data scientists and energy engineers, you will bring forecasting and optimization models into our EMS production environment (Cloud and Edge). You will maintain and improve ML pipelines (using tools like Prefect and MLFlow) to support the full model lifecycle—from experiment tracking to training and validation. You will ensure feature engineering for time-series, asset telemetry, and market data is robust, monitor model quality, handle concept drift, and evaluate performance. You will lead the development of digital twins and simulation environments to test EMS interactions with hardware before deployment. Collaboration with embedded and platform teams to integrate your work into GreenBox edge devices and backend services is also part of your role. While we are still considered pioneers today, we can soon dominate the market with you! First in the DACH region, then throughout Europe. You can expect a motivated, open-minded, and dynamic environment passionate about actively shaping the energy transition—a goal that can only be achieved together! We look forward to your application – Fernanda will get in touch with you!