Machine Learning Engineer - BC

Machine Learning Engineers develop and deploy ML models for industrial process environments, including fault detection, predictive maintenance, and quality optimization. They work across the full project lifecycle, from scoping problems with plant engineers to deploying and monitoring models in production. The role requires strong Python skills and experience with various ML frameworks, as well as Docker and Kubernetes for containerization.

• Develop and deploy ML models (classification, regression, anomaly detection, time-series forecasting) for industrial process applications
• Collaborate with process engineers and operators to translate domain problems into well-scoped ML tasks
• Build robust data pipelines from historians, SCADA systems, and other industrial data sources
• Design feature engineering strategies grounded in physical process understanding
• Validate models against real plant conditions
• Containerize and deploy models using Docker and Kubernetes
• Support model monitoring, retraining workflows, and CI/CD for ML pipelines

• Degree in Engineering (Electrical, Mechanical, Chemical, or similar), Computer Science, or related field
• 3-5 years of applied ML or data science experience, ideally in manufacturing or process industries
• Strong Python skills with scikit-learn, pandas, NumPy