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 on cutting-edge ML applications in manufacturing, including predictive maintenance, computer vision, and forecasting. You'll be responsible for building end-to-end ML solutions using modern tools and frameworks like PyTorch, TensorFlow, and Azure ML services. The role combines technical expertise in ML engineering with practical applications in manufacturing processes.
This is an excellent opportunity for an experienced ML engineer looking to make a real impact in industrial automation and smart manufacturing. You'll work with a global, diverse team and have the chance to influence manufacturing processes across multiple continents. The company offers a collaborative environment focused on innovation and continuous learning, with opportunities to upskill factory engineers and operators.
Johnson Electric's commitment to improving quality of life through innovative motion systems, combined with their inclusive culture and global presence, makes this an ideal position for someone passionate about applying ML to real-world manufacturing challenges. The role offers the perfect blend of technical ML work and practical industrial applications, with the backing of a major global manufacturer.
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 hands-on problem solving ability
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