Machine Learning Engineer
Description For Machine Learning Engineer
Johnson Electric, a global leader in motion solutions, is seeking a Machine Learning Engineer to join their Smart Factory initiative. This role is part of a high-impact Center of Excellence team that manages the complete analytical stack, from edge data acquisition to model deployment. The position offers an opportunity to work on production-grade AI use-cases across 30+ plants on five continents.
The ideal candidate will be responsible for developing and deploying machine learning solutions that drive zero-defect quality and lights-out manufacturing. You'll work with cutting-edge technologies including PySpark, PyTorch, TensorFlow, and cloud services while implementing MLOps best practices. The role combines technical expertise in ML with practical applications in manufacturing.
As part of Johnson Electric's global team of 35,000+ employees across 22 countries, you'll contribute to improving the quality of life through innovative motion systems. The company values diversity and inclusion, providing an environment where employees from different backgrounds are valued and respected. This position offers the chance to work on meaningful projects that directly impact manufacturing efficiency and quality while being part of a company that serves major brands in automotive, industrial, and consumer markets.
The role requires strong technical skills in Python, ML frameworks, and cloud services, combined with the ability to collaborate effectively with product owners and factory engineers. You'll be responsible for the entire ML lifecycle, from problem definition to model deployment and monitoring, making this an excellent opportunity for someone passionate about applying AI in industrial settings.
Responsibilities For Machine Learning Engineer
- Translate business problems into ML tasks: predictive maintenance, image segmentation and classification, price quotation and forecasting
- Build data pipelines (PySpark, Synapse, Databricks) and feature engineering workflows
- Train, fine-tune, and evaluate ML models using scikit-learn, XGBoost, PyTorch, TensorFlow
- Containerize models and deploy to AKS/edge devices via automated CI/CD pipelines
- Establish monitoring suite for model and data drift
- Apply MLOps best practices
- Co-create user stories with product owners and deliver incremental value in sprints
- Produce clean, test-covered, well-documented code
- Conduct workshops and demos to upskill factory engineers & operators
Requirements For Machine Learning Engineer
- 3-5 years hands-on experience in ML engineering or data science deploying models to production
- Solid foundation in traditional ML, statistics, and experimentation
- Solid Python programming; experience with unit/integration testing frameworks
- Practical knowledge of containerization (Docker) and basic Kubernetes concepts
- Familiarity with Azure ML or comparable cloud ML services
- Familiarity with Generative frameworks like LangChain, LlamaIndex
- Understanding CI/CD & IaC workflows
- Strong communication skills and hands-on problem solving
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