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 focuses on delivering production-grade AI solutions that drive zero-defect quality and lights-out manufacturing across 30+ plants globally.
The ideal candidate will work at the intersection of manufacturing and artificial intelligence, developing and deploying machine learning solutions for predictive maintenance, computer vision, and forecasting. You'll be responsible for building robust data pipelines, training and deploying models, and establishing MLOps practices to ensure reliable scaling of AI solutions.
This is an excellent opportunity for a mid-level ML engineer who wants to make a tangible impact in industrial automation and smart manufacturing. You'll work with cutting-edge technologies while solving real-world problems in a global manufacturing environment. The role offers exposure to diverse projects and the chance to influence the digital transformation of a major industrial player.
The company offers a truly global, inclusive work environment where diversity is valued and employees can find fulfillment in their work. As part of Johnson Electric's mission to improve quality of life through innovative motion systems, you'll be contributing to transformative solutions that impact various industries from automotive to medical devices.
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
- Co-create user stories with product owners and deliver value in sprints
- Produce clean, test-covered, well-documented code
- Conduct workshops 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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