ML Engineer - Predictive Maintenance

Your Position

You will work as a Data Engineer with Machine Learning expertise in the Predictive Maintenance team. This hybrid and multi-cultural team includes Data Scientists, Machine Learning Engineers, Data Engineers, a DevOps Engineer, a QA Engineer, an Architect, a UX Designer, a Scrum Master, and a Product Owner.

The Digital Service Platform focuses on optimizing customer asset usage and maintenance, impacting performance, cost, and sustainability KPIs by extending component lifetimes.

In your role, you will:

• Participate in solution design discussions led by our Product Architect, where your input as a Data Engineer with ML expertise is highly valued.
• Collaborate with IT and business SMEs to ensure delivery of high-quality end-to-end data and machine learning pipelines.

Your Responsibilities

Data Engineering

• Develop, test, and document data (collection and processing) pipelines for Predictive Maintenance solutions, including data from (IoT) sensors and control components to our data platform.
• Build scalable pipelines to transform, aggregate, and make data available for machine learning models.
• Align implementation efforts with other back-end developers across multiple development teams.

Machine Learning Integration

• Collaborate with Data Scientists to integrate machine learning models into production pipelines, ensuring smooth deployment and scalability.
• Develop and optimize end-to-end machine learning pipelines (MLOps) from data preparation to model deployment and monitoring.
• Work on model inference pipelines, ensuring efficient real-time predictions from deployed models.
• Implement automated retraining workflows and ensure version control for datasets and models.

Continuous Improvement

• Contribute to the design and build of a CI/CD pipeline, including integration test automation for data and ML pipelines.
• Continuously improve and standardize data and ML services for customer sites to reduce project delivery time.
• Actively monitor model performance and ensure timely updates or retraining as needed.

Your Profile

• Minimum 4 years' experience building complex data pipelines and integrating machine learning solutions.
• Bachelor's or Master's degree in Computer Science, IT, Data Science, or equivalent.
• Hands-on experience with data modeling and machine learning workflows.
• Strong programming skills in Java, Scala, and Python (preferred for ML tasks).
• Experience with stream processing frameworks (e.g., Spark) and streaming storage (e.g., Kafka).
• Proven experience with MLOps practices, including data preprocessing, model deployment, and monitoring.
• Familiarity with ML frameworks and tools (e.g., TensorFlow, PyTorch, MLflow).
• Proficient in cloud platforms (preferably Azure and Databricks).
• Experience with data quality management, monitoring, and ensuring robust pipelines.
• Knowledge of Predictive Maintenance model development is a strong plus.

What Youll Gain

• Opportunity to work at the forefront of data-driven innovation in a global organization.
• Collaborate with a talented and diverse team to design and implement cutting-edge solutions.
• Expand your expertise in data engineering and machine learning in a real-world industrial setting.

If you are passionate about leveraging data and machine learning to drive innovation, wed love to hear from you!