Machine Learning Engineer
Green Fusion
full-time
Posted on:
Location Type: Hybrid
Location: Berlin • Germany
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About the role
- 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.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
Pythonmachine learning engineeringtime-series forecastingnonlinear optimizationstochastic model predictive controlprobabilistic forecastingReinforcement LearningMLOpsfeature engineeringmodel quality monitoring
Soft skills
collaborationcommunicationcuriosityleadership