Machine Learning Engineer

• You will design and improve machine learning models for time-series forecasting and nonlinear optimization, taking them from concept to deployment.
• By working alongside data scientists and energy engineers, you will 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. You ensure feature engineering for time-series, asset telemetry, and market data is robust. You also 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.
• You will collaborate with embedded and platform teams to integrate your work into the GreenBox edge device and backend services.

We know that nobody fits a job description 100%. If you see yourself in most of these points and are passionate about our mission, we'd love to hear from you!

• You bring a strong background in Python and machine learning engineering, with hands-on experience developing, testing, and maintaining models in containerized production environments (e.g., Docker, AWS).
• You are familiar with the full machine-learning lifecycle, from training to deployment and monitoring, and you have experience using MLOps tools such as Prefect, MLflow, or similar platforms.
• You have experience in time-series forecasting and nonlinear optimization, and ideally you've worked with stochastic model predictive control or probabilistic forecasting techniques.
• You are curious about how physical and energy systems work, from heat pumps to power markets, and you recognize the importance of validating algorithms that control real-world hardware.
• You enjoy collaborating with cross-functional teams (Energy, Backend, Embedded) and can clearly communicate technical concepts to diverse stakeholders.
• Bonus Points: You bring experience with Reinforcement Learning, IoT/Edge deployments, or energy management systems (EMS)-a plus, but not a must.

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 that is passionate and ambitious 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! Teilen