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 CoE 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, implementing solutions for predictive maintenance, computer vision, and advanced analytics.
The ideal candidate will be responsible for developing and deploying production-grade AI solutions, building robust data pipelines, and implementing MLOps practices. You'll work with modern tools and technologies including PyTorch, TensorFlow, Azure ML, and Kubernetes, while collaborating with cross-functional teams to drive zero-defect quality and lights-out manufacturing across 30+ global plants.
This role combines technical expertise in machine learning with practical industrial applications, offering the chance to make a direct impact on manufacturing 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 services, combined with the ability to communicate effectively with stakeholders. You'll have the opportunity to shape the future of smart manufacturing while working in a collaborative environment that promotes continuous learning and professional growth.
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 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 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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