Hybrid Machine Learning Engineer

Posted last week

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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.

Job title

Machine Learning Engineer

Job type

Experience level

Mid levelSenior

Salary

Not specified

Degree requirement

Bachelor's Degree

Location requirements

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