Hybrid Machine Learning Engineer

at Green Fusion

• Job title: Machine Learning Engineer
• Job type: Full Time
• Experience level: Mid level, Senior
• Salary: Not specified
• Degree requirement: Bachelor's Degree
• Tech skills: AWS, Cloud, Docker, IoT, Python
• Location requirements: Hybrid, Berlin, Germany

About the role

• Machine Learning Engineer at Green Fusion developing intelligent Energy Management Systems to combat climate change. Collaborating with cross-functional teams for model optimization and deployment.

Responsibilities

• 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.

Requirements

• Strong background in Python and machine learning engineering.
• Hands-on experience developing, testing, and maintaining models in containerized production environments (e.g., Docker, AWS).
• Familiarity with the full machine-learning lifecycle, from training to deployment and monitoring.
• Experience using MLOps tools such as Prefect, MLflow, or similar platforms.
• Experience in time-series forecasting and nonlinear optimization.
• Ideally experienced with stochastic model predictive control or probabilistic forecasting techniques.
• Curious about how physical and energy systems work, from heat pumps to power markets.
• Enjoy collaborating with cross-functional teams (Energy, Backend, Embedded) and can clearly communicate technical concepts to diverse stakeholders.
• Bonus Points: Experience with Reinforcement Learning, IoT/Edge deployments, or energy management systems (EMS).

Benefits

• Flexible working hour models, home office, and remote work.
• Ongoing training opportunities – whether through job challenges, our open feedback culture, or sponsored training programs, there are always opportunities to learn and grow.
• Employee benefits such as Urban Sports Club or Become1.
• Direct impact through your job – with us, you can actively contribute to the energy transition and fight against climate change every day.
• We value our team – that's why regular team events are very important to us.
• The best team that Berlin has to offer – and maybe even beyond.