Machine Learning Engineer
Job Description
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 cutting-edge AI applications in manufacturing, leveraging advanced analytics and IIoT across 30+ plants globally.
The ideal candidate will be responsible for developing and deploying production-grade AI solutions, focusing on use cases like predictive maintenance, image processing, and forecasting. You'll work with modern tools and technologies including PyTorch, TensorFlow, and cloud services, while implementing MLOps best practices for model deployment and monitoring.
This role combines technical expertise in machine learning with practical manufacturing applications, offering the chance to directly impact production efficiency and quality. You'll be part of a global, inclusive team that values diversity and innovation, working for a company that serves major brands in automotive, industrial, and consumer markets.
The position requires strong technical skills in Python, ML frameworks, and cloud technologies, combined with the ability to collaborate effectively with stakeholders. You'll have the opportunity to contribute to Johnson Electric's mission of improving quality of life through innovative motion systems while working in a supportive environment that encourages professional growth and values diverse perspectives.
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 manufacturing process knowledge
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