About Powerchainger
We are a climate tech startup located at Zernike Campus Groningen. At Powerchainger we are passionate about energy and technology. With a small and highly motivated team, we develop cutting-edge AI software for using energy in an optimal way and bringing the waste of electricity to a minimum. Currently we are at the stage of Product Soft Launch, developing an MVP for market. With our product, we are ready to build a smarter, fairer, and more sustainable energy system.
About the job
We’re looking for an experienced Machine Learning engineer to join our team and help shape the future of energy intelligence. In this role, you will contribute to the development of our Non-Intrusive Load Monitoring (NILM) models and the maintenance of our entire machine learning pipeline. You will play a key role in establishing our Machine Learning Operations (MLOps), ensuring that our ML stack is robust, scalable, and production-ready. This includes working with time-series data, training and refining models, and collaborating cross-functionally to integrate intelligent solutions into our product.
Key Responsibilities
- Develop and optimize machine learning models, with a focus on Non-Intrusive Load Monitoring (NILM).
- Analyze and process large volumes of time-series data from domestic energy consumption.
- Design, implement, and maintain end-to-end machine learning pipelines.
- Lead the development of MLOps infrastructure.
- Set up tooling and best practices for reproducibility, experiment tracking, and model governance (e.g. using MLflow, DVC, Weights & Biases).
- Collaborate with product and engineering team to integrate models into production environments.
- Monitor model performance in production and iterate based on user feedback and new data.
You’ll be a perfect match if
- Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or any other related field.
- 3+ years experience as Machine Learning Engineer or Data Scientist.
- Strong machine learning background and familiarity with the underlying concepts of neural networks.
- Practical experience working with time-series data.
- Proficiency in Python and ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
- Hands-on experience with MLOps, including CI/CD pipelines, containerization (Docker), orchestration (Airflow/Kubeflow), and deployment (e.g. Kubernetes, SageMaker, or custom infra).
- Familiarity with experiment tracking and model versioning tools.
- Excellent communication skills in English.
Nice to have
- Experience with Non-Intrusive Load Monitoring (NILM).
- Research (oriented) background.
- Experience in the energy sector.
This is what we offer
- 0,8-1,0 FTE position at our office at Zernike Campus Groningen.
- Being part of a lean, diverse and highly motivated team.
- Appropriate salary.
- A vibrant work space and autonomy for personal growth, with a direct impact on our success.
- Opportunity to take responsibility and ownership of your work.
- Flexible working hours (perfect for both night owls and early birds).
- A table tennis table to help you stay “focussed” (strategically procrastinate).
- Option to work remotely.