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 leveraging advanced analytics, AI, and IIoT to achieve zero-defect quality and sustainable manufacturing operations across 30+ global plants.
The position offers a unique opportunity to work on production-grade AI use-cases, from edge data acquisition to model deployment. You'll be responsible for developing and implementing machine learning solutions for predictive maintenance, image processing, and forecasting applications. The role requires expertise in Python, modern ML frameworks, and cloud technologies, with a focus on MLOps practices and production deployment.
As a Machine Learning Engineer, you'll work with cutting-edge technologies including PyTorch, TensorFlow, and cloud services while collaborating with cross-functional teams to deliver tangible business impact. The position requires 3-5 years of experience and offers the chance to work in a truly global, inclusive environment that values diversity and innovation.
The company's commitment to improving quality of life through innovative motion systems, combined with their strong market position in automotive, industrial, and consumer markets, makes this an excellent opportunity for ML professionals looking to make a real impact in manufacturing technology. The role offers professional growth, hands-on problem-solving opportunities, and the chance to be part of a transformative Smart Factory initiative.
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
- 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
Benefits For Machine Learning Engineer
- Inclusive and diverse workplace
- Global team environment
- Professional growth opportunities
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