Machine Learning Engineer (m/w/d)
Core
Building, stabilizing, and operating a production Predictive Maintenance AI/ML product with a focus on MLOps, feature engineering, and model lifecycle management.
Role type
Machine Learning Engineer (MLOps & Predictive Maintenance)
Builds
Production ML models and data processing pipelines for predictive maintenance in the energy grid sector.
Domain
Energy infrastructure / Industrial IoT / Predictive Maintenance
Deliverable
production ML models | product features | infrastructure
Required skills
Python, PySpark/Spark SQL, ETL/ELT pipeline development, Azure cloud platforms, Delta Lake, Unity Catalog, SQL databases, REST APIs, Feature Engineering, Model Evaluation, Retraining, Cluster Management, Job/Workflow orchestration, Error analysis, SAP/GIS data handling
Preferred skills
Databricks production experience, technical documentation, cross-functional collaboration
Technologies
Azure, Databricks, PySpark, Spark SQL, Delta Lake, Unity Catalog, SAP, GIS, REST, Python
Responsibilities
Develop, stabilize, and operate a production AI/ML product including monitoring in the Predictive Maintenance environment. Actively contribute to feature engineering, retraining, evaluation, and quality assurance of ML models. Maintain and optimize ML and data pipelines in Databricks including jobs, workflows, cluster management, and error analysis. Extend existing data processing pipelines using Python, PySpark/Spark SQL, Delta Lake, and SAP/GIS data sources. Coordinate closely with business units, IT, Data Science, and operations to ensure clean documentation and clear handovers.
Seniority
Mid-level, hands-on IC
