Machine Learning Engineer Intern contributing to AI solutions for financial services. Engaging in hands - on ML projects and real production issues in a hybrid working environment.
About the role
- Machine Learning Engineer supporting the development of intelligent Energy Management Systems. Collaborating on model predictions and optimizations to advance energy transition technology.
Responsibilities
- Support the Sector Coupling team in building the next generation of intelligent Energy Management Systems (EMS).
- Enable high-accuracy model predictions and optimizations through long-term learning from data.
- Design and improve machine learning models for time-series forecasting and nonlinear optimization.
- Deploy forecasting and optimization models into the EMS production environment (Cloud and Edge).
- Maintain and improve ML pipelines (using tools like Prefect and MLflow).
- Ensure robust feature engineering for time-series, asset telemetry, and market data.
- Lead monitoring of model quality, addressing concept drift and evaluating performance.
- Lead the development of digital twins and simulation environments to safely test EMS interactions before deployment to real hardware.
- Collaborate with embedded and platform teams to integrate solutions into the GreenBox edge device and backend services.
Requirements
- Strong experience 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 through deployment and monitoring.
- Experience using MLOps tools such as Prefect, MLflow, or similar platforms.
- Experience in time-series forecasting and nonlinear optimization.
- Ideally, experience with stochastic model predictive control or probabilistic forecasting techniques.
- Curiosity about how physical and energy systems operate, from heat pumps to power markets.
- Enjoy working with cross-functional teams (Energy, Backend, Embedded) and can clearly communicate technical concepts to diverse stakeholders.
- Bonus: Experience with Reinforcement Learning, IoT/Edge deployments, or energy management systems (EMS) – a plus but not required.
Benefits
- Flexible working hours, home office, and remote work options.
- Ongoing training opportunities – through on-the-job challenges, an open feedback culture, or sponsored training programs.
- Employee benefits such as Urban Sports Club or Become1.
- Direct impact through your work – contribute actively to the energy transition and combat climate change every day.
- We value our team – regular team events are important to us.
- Join one of the best teams Berlin has to offer – and possibly beyond.
Job title
Job type
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Degree requirement
Tech skills
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