Machine Learning Engineer Process Optimization

Position: Machine Learning Engineer for Process Optimization
Lead machine learning projects as an Engineer focused on optimizing industrial processes and deployment of predictive models. Your work will enhance efficiency and quality across operations.
This role involves engaging with engineers to define ML scope, wrangling complex sensor data, and deploying models that cater to fault detection and maintenance. Utilize Docker and Kubernetes for containerization while ensuring model validation through actual plant conditions and effective CI/CD practices.

Key Responsibilities:

• Develop and implement ML models for industrial uses

• Collaborate with engineers to scope ML tasks effectively

• Build data pipelines from industrial data sources

• Validate models against operating conditions

• Manage model deployment with Docker and monitoring tools
Requirements:

• Advanced degree in a technical field

• 3-5 years in machine learning or data science

• Expertise in Python and ML libraries

• Familiar with time-series data handling

• Clear communication of ML implications to stakeholders
Apply your skills to drive innovation and efficiency in machine learning applications within industrial settings.
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