Machine Learning Engineer
Job Description
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 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, working with modern tools and frameworks including PyTorch, TensorFlow, and cloud services. You'll be part of a team that's driving zero-defect quality and lights-out manufacturing across 30+ plants on five continents. The role combines technical expertise in machine learning with practical applications in industrial settings.
This position offers the chance to work in a truly global, inclusive environment where diversity is valued and employees are encouraged to grow. You'll be implementing MLOps best practices, working with state-of-the-art technology stacks, and directly impacting manufacturing efficiency through AI solutions. The company's commitment to improving quality of life through innovative motion systems makes this an exciting opportunity for someone passionate about applying ML to real-world industrial challenges.
The role requires both technical excellence and strong collaboration skills, as you'll be working closely with product owners and factory engineers. Johnson Electric's position as a major provider to automotive, industrial, and consumer markets means your work will have significant impact across multiple industries. This is an ideal opportunity for an ML engineer looking to apply their skills in a manufacturing context while working for a global industry leader.
Responsibilities For Machine Learning Engineer
- Translate business problems into ML tasks including 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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