Machine Learning Engineer

About the role

Johnson Electric, a global provider of motion solutions, is hiring a Machine Learning Engineer in Jiangmen to join its Smart Factory CoE team. The team owns the full analytical stack, from edge data acquisition and cloud ingestion to model deployment and smart factory adoption, and aims to accelerate delivery of production-grade AI use cases.

Key responsibilities

• Translate business problems into ML tasks such as 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 (scikit-learn, XGBoost, PyTorch, TensorFlow) using experiment tracking (MLflow).
• Containerize models and deploy them to AKS and edge devices via automated CI/CD pipelines (AML pipelines, Azure DevOps).
• Set up monitoring (Prometheus, Grafana, PromptFlow) for model and data drift, and apply MLOps patterns such as provenance, reproducibility, automated retraining and rollback.
• Work with product owners in sprints, write clean, tested and documented code, take part in peer reviews, and run workshops and demos for factory engineers and operators.

Required profile

• 3 to 5 years of hands-on experience in ML engineering or data science deploying models to production.
• Solid foundation in traditional ML, statistics and experimentation (p-values, A/B tests, power analysis).
• Strong communication skills, curiosity about manufacturing processes and a hands-on approach.

Required skills

• Solid Python, including unit and integration testing (pytest)
• Docker and basic Kubernetes concepts
• Azure ML or comparable cloud ML services
• Generative frameworks such as LangChain and LlamaIndex for agentic flows
• CI/CD and IaC (Git, GitHub Actions or Azure DevOps, Terraform/Bicep)