Machine Learning Engineer
Job Description
At our company, we are at the forefront of the digitalization and energy transition sectors. Our innovative software is designed to comprehensively optimize energy systems within the real estate industry, playing a crucial role in the fight against climate change through effective digitalization and automation strategies. As a Machine Learning Engineer, you will be an integral part of our Sector Coupling team, tasked with developing the next generation of intelligent Energy Management Systems (EMS). Your primary focus will be on enabling precise model predictions and optimizations by leveraging long-term learning from our extensive data sets to promote energy savings on a daily basis. You will take the lead in designing and refining machine learning models aimed at time-series forecasting and nonlinear optimization, transitioning them smoothly from conceptual stages to full production deployment. Your collaboration with data scientists and energy engineers will be vital as you integrate forecasting and optimization models into our EMS production environment, both in cloud and edge computing contexts. Furthermore, you will maintain and enhance our machine learning pipelines, utilizing tools such as Prefect and MLFlow to support the entire model lifecycle, from tracking experiments to training and validating models. You will act as the custodian of our data, ensuring rigorous feature engineering for time-series, asset telemetry, and market data, while also monitoring model quality to address concept drift and evaluate performance. Additionally, you will lead the creation of digital twins and simulation environments to safely assess how our EMS interacts with hardware components prior to real-world application. Collaboration with embedded systems and platform teams will be essential to effectively integrate your solutions into our GreenBox edge device and backend services.
Key Responsibilities
As a Machine Learning Engineer, you will engage in various critical tasks to support the development and optimization of our energy management systems.
- Design and enhance machine learning models for time-series forecasting and optimization
- Deploy models into production environments
- Maintain ML pipelines with tools like Prefect and MLFlow
- Ensure robust feature engineering for various data types
- Monitor model performance and handle concept drift
- Develop digital twins and simulation environments
- Collaborate with cross-functional teams to integrate solutions
Required Technical Skills
Soft Skills
Qualifications
- Strong background in Python
- Experience in machine learning engineering
- Hands-on development and maintenance of models in containerized production environments
Language Requirements
Programming Languages:
Python, SQL
Spoken Languages:
English, German
Benefits & Perks
- ✓ Flexible working hours and remote work options
- ✓ Ongoing training and development opportunities
- ✓ Employee benefits like Urban Sports Club membership
- ✓ Direct impact on the energy transition
- ✓ Regular team events to foster camaraderie
Working Conditions
Full Time
Company Culture
We foster a motivated and dynamic work environment where innovation thrives. Our team is passionate about making a tangible difference in the energy sector and values collaboration and open communication.
Salary Range
Project Types: Not Available
Career Growth: Career growth through training programs, Possibility to take on leadership roles in projects