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 offers an opportunity to work on cutting-edge AI applications in manufacturing, leveraging advanced analytics and IIoT to achieve zero-defect quality and lights-out manufacturing across 30+ global plants.
The ideal candidate will be responsible for developing and deploying production-grade AI solutions, working with technologies like PyTorch, TensorFlow, and cloud services. They will handle everything from data pipeline construction to model deployment and monitoring, while following MLOps best practices. The role requires a blend of technical expertise in machine learning, software engineering, and DevOps practices, along with the ability to collaborate effectively with product owners and factory engineers.
This position offers the unique opportunity to impact manufacturing processes at a global scale, working within a diverse and inclusive team environment. Johnson Electric's commitment to improving quality of life through innovative motion systems makes this an ideal role for someone passionate about applying AI to real-world manufacturing challenges. The company's strong presence in automotive, medical devices, and various industrial markets provides exposure to diverse applications of machine learning in manufacturing.
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
- 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 (Docker) 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
- Curiosity to learn manufacturing processes
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