Senior Machine Learning Engineer

About Powerchainger

Powerchainger is a fast-moving (early-stage) energy tech startup based in Groningen, turning data into real-time appliance-level insights to optimize energy consumption, improve forecasting, and grow customer value. We’re building cutting-edge AI that drives real impact for both people, planet, and business – and we’re looking for someone bold enough to help us scale it to the next level.

What 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’ll take the lead in advancing our models for Non-Intrusive Load Monitoring and Demand Forecasting, while ensuring the robustness and scalability 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 NILM.
• Develop and optimize machine learning models for Demand Forecasting.
• 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.
• Collaborate with product and engineering teams to integrate models into production environments.
• Monitor model performance in production and iterate based on user feedback and new data.

Your profile

• Master’s or PhD in Computer Science, Data Science, Artificial Intelligence or any other related field.
• 5+ years of experience as a Machine Learning Engineer or Data Scientist, preferably (partially) in a lead role.
• 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.
• Strong written and oral communication skills in English.

Advantageous:

• Experience with Non-Intrusive Load Monitoring (NILM) and forecasting models.
• Strong research background.
• Proven experience in the energy domain.

What we offer

• €4,000 to €6,000 per month, based on a 40-hour contract and experience.
• One-year renewable contract.
• Participation in our Employee Incentive Program.
• Hybrid setup with 1-2 days a week in the office (depending on where you live).
• Laptop and professional development budget.
• Collaborative, inspiring, and dynamic environment.
• A real opportunity to shape the growth of a fast-moving energy tech startup (and share in its success).

Process

We love go-getters! Our hiring process includes an assessment and reference check. Impress us, and you’re in.

Ready to make a real impact?

Please send your CV and a motivation letter to info@powerchainger.nl.

For any questions about the role, you can also contact Marios Souroulla, Co-Founder and CTO, using the same email address.