Machine Learning Engineer
Description For Machine Learning Engineer
Johnson Electric, a global leader in motion solutions with over 35,000 employees across 22 countries, 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 exciting opportunity to work on production-grade AI use-cases, leveraging advanced analytics and IIoT to achieve zero-defect quality and sustainable operations across 30+ global plants. You'll be responsible for developing and deploying machine learning solutions for predictive maintenance, image processing, and forecasting applications.
As a Machine Learning Engineer, you'll work with cutting-edge technologies including PyTorch, TensorFlow, and cloud services while implementing MLOps best practices. The role combines technical expertise in ML engineering with practical application in manufacturing, offering a unique chance to impact real-world industrial processes.
The ideal candidate should have 3-5 years of hands-on ML engineering experience, strong Python programming skills, and familiarity with modern ML frameworks and cloud services. This position offers the opportunity to join a diverse, global team committed to improving quality of life through innovative motion systems.
Johnson Electric provides an inclusive workplace where employees from different backgrounds are valued and respected, offering opportunities for growth and meaningful work in a truly global environment.
Responsibilities For Machine Learning Engineer
- Translate business problems into ML tasks: predictive maintenance, image segmentation and classification, price quotation and forecasting
- Build data pipelines using 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
- Collaborate with product owners and deliver value in sprints
- Produce clean, test-covered, well-documented code
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 and basic Kubernetes concepts
- Familiarity with Azure ML or comparable cloud ML services
- Familiarity with Generative frameworks like LangChain, LlamaIndex
- Understanding of CI/CD & IaC workflows
- Strong communication skills and hands-on problem solving
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