Machine Learning Engineer, Breda, Noord-Brabant

Company
The client is an innovative manufacturing organization focused on improving production performance through smart digital technologies. The business invests in data-driven solutions, advanced automation, and modern engineering methods to improve equipment reliability, operational efficiency, and manufacturing quality.

Job Description:
We are seeking a skilled Machine Learning Engineer to join our client’s team, supporting their efforts to implement smart automation and predictive maintenance in manufacturing environments. The successful candidate will analyze equipment and process data to develop models that improve equipment reliability and operational performance, contributing to the evolution of industrial AI applications.

Responsibilities:
- Manage the entire lifecycle of machine learning models—from data collection, preprocessing, and development to deployment, validation, and ongoing enhancement.
- Gather and analyze data from various industrial systems such as compressors, pumps, and manufacturing machinery, interpreting signals like vibration, temperature, and images.
- Research and recommend suitable machine learning and deep learning techniques for different use cases.
- Develop and train models for condition monitoring, predictive maintenance, and anomaly detection.
- Build production-grade Python pipelines for training, testing, and deploying models within manufacturing settings.
- Design dashboards using tools like Grafana to visualize data and model outputs effectively.
- Regularly evaluate and monitor models to ensure accuracy, stability, and long-term performance.
- Collaborate with different technical teams, including automation engineers and external vendors, to ensure solutions meet operational needs and standards.

Requirements:
- MSc in Computer Science, Machine Learning, Mechatronics, or related fields with at least 3 years of relevant experience, or BSc with at least 5 years of experience.
- Strong programming skills in Python and familiarity with platforms such as Databricks.
- Knowledge of anomaly detection, probabilistic models, and practical deployment of machine learning solutions.
- Ability to interpret sensor data from industrial equipment (pumps, compressors, etc.).
- Experience in software engineering and DevOps practices, including Git, Docker, and CI/CD workflows.
- Capable of independently designing and executing end-to-end machine learning projects.
- Fluent in English, both spoken and written.

Other Information:
If you are interested and want to apply, please submit your application via the apply button below and contact me.

 

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