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 responsible for implementing AI and advanced analytics solutions across their manufacturing operations.
The position offers a unique opportunity to work on cutting-edge ML applications in industrial automation, focusing on predictive maintenance, computer vision, and smart manufacturing solutions. You'll be responsible for the entire ML lifecycle - from data pipeline construction to model deployment and monitoring.
The ideal candidate should have 3-5 years of hands-on ML engineering experience, strong Python programming skills, and practical knowledge of modern MLOps practices. Experience with cloud platforms (particularly Azure), containerization, and CI/CD workflows is essential. You'll work with technologies like PyTorch, TensorFlow, and Kubernetes while implementing solutions that directly impact manufacturing efficiency.
This role is perfect for someone who combines technical expertise with business acumen and enjoys solving complex real-world problems. You'll be part of a global team that values diversity and inclusion, with opportunities to influence manufacturing processes across 30+ plants worldwide. The position offers the chance to work on meaningful projects that improve manufacturing quality and efficiency while developing your skills in an innovative, forward-thinking environment.
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 for model lifecycle management
- 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
Benefits For Machine Learning Engineer
- Global, inclusive & diverse team environment
- Professional growth opportunities
- Meaningful work impact
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