About the Role
Machine Learning Engineer – Industrial Process Environment
Work across the full project lifecycle: scoping problems with plant engineers, wrangling messy sensor data, building and deploying models, and ensuring they work in production for fault detection, predictive maintenance, quality optimization, and process control. Reports To
Operations Director Responsibilities
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, not just offline metrics. Containerize and deploy models using Docker, with experience in Kubernetes or similar orchestration tools. S...
Work across the full project lifecycle: scoping problems with plant engineers, wrangling messy sensor data, building and deploying models, and ensuring they work in production for fault detection, predictive maintenance, quality optimization, and process control. Reports To
Operations Director Responsibilities
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, not just offline metrics. Containerize and deploy models using Docker, with experience in Kubernetes or similar orchestration tools. S...
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