Johnson Electric is one of the world’s largest providers of motion solutions, supplying nearly every major brand in automotive, industrial, and consumer markets. Our Smart Factory initiative leverages advanced analytics, AI and IIoT to drive zero-defect quality, lights-out manufacturing, and sustainable operations across 30+ plants on five continents.
You will be joining a high-impact, hands-on CoE team that owns the full analytical stack: from edge data acquisition and cloud ingestion to model deployment and smart factory adoption.
Accelerate delivery of production-grade AI use-cases. You will prototype, train, and deploy models (classical as well as deep learning) on top of Cloud services and ensure they stay reliable at scale.
Use-Case Delivery
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Translate business problems into ML tasks: predictive maintenance, image segmentation and classification, price quotation and forecasting, etc.
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Build data pipelines (PySpark, Synapse, Databricks) and feature engineering workflows.
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Train, fine-tune, and evaluate ML models (scikit-learn, XGBoost, PyTorch, TensorFlow) following experiment-tracking standards (MLflow).
Model Deployment & Lifecycle Management
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Containerize models; Deploy to AKS/edge devices via automated CI/CD pipelines (AML pipelines, Azure DevOps).
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Establish monitoring suite (Prometheus, Grafana, PromptFlow) for model, and data drift.
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Apply best-practice MLOps patterns: provenance, reproducibility, automated retraining, and rollback strategies.
Collaboration & Agile Delivery
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Co-create user stories with product owners, size tasks, and deliver incremental value in sprints.
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Produce clean, test-covered, well-documented code; participate in peer reviews.
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Conduct workshops and demos to upskill factory engineers & operators.
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3 – 5 years hands-on experience in ML engineering or data science deploying models to production.
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Solid foundation in traditional ML, statistics, and experimentation (p-values, A/B, power analysis).
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Solid Python programming; experience with unit/integration testing frameworks (pytest).
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Practical knowledge of containerization (Docker) and at least basic Kubernetes concepts (pods, services, config-maps, secrets).
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Familiarity with Azure ML or comparable cloud ML services.
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Familiarity with Generative frameworks like LangChain, LlamaIndex etc to implement Agentic Flows
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Understanding CI/CD & IaC workflows (Git, GitHub Actions or Azure DevOps, Terraform/Bicep).
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Strong communication skills, curiosity to learn manufacturing processes, and bias for hands-on problem solving.
Come join our global, inclusive & diverse team
Our purpose is to improve the quality of life of everyone we touch through our innovative motion systems. We are a truly global team bound together by our shared values. Our culture is built on the diversity, knowledge, skills, creativity, and talents that each employee brings to the company. Our people are our company’s most valuable asset. We are committed to providing an inclusive, diverse and equitable workplace where employees of different backgrounds feel valued and respected, regardless of their age, gender, race, ethnicity or religious background. We are committed to inspiring our employees to grow, act with ownership and find fulfilment and meaning in the work they do.
欢迎加入我们全球性、富包容和多元化的团队！
我们的目标是通过创新的驱动系统提高每一个产品接触者的生活质量。我们是一个真正的全球性团队，我们有着共同的价值观因而联结在一起。我们的文化是建基于每一位员工为公司带来的多样性、知识、技能、创意和才能之上。我们的员工是我们企业最宝贵的资产。我们致力于为员工提供一个包容、多元和平等的工作场所，在这里无论他们的年龄、性别、肤色、种族或宗教信仰如何，不同背景的员工都能感到受重视和尊重。我们致力于激励我们的员工成长，以主人翁精神行事，并在他们所做的工作中找到成就感和意义。
