Engineering Trainee, Process AI & Data Analyst (Based in Jiangmen)
Johnson Electric Industrial Manufactory Limited Engineering Trainee, Process AI & Data Analyst (Based in Jiangmen)
Summary
Engineering trainee role at Johnson Electric, based in Jiangmen, building AI-driven closed-loop process control for injection molding machines plus end-to-end manufacturing data pipelines and Power BI dashboards, while upskilling the local team in Python, SQL, LLM/RAG and Azure AI Studio. Fresh graduates welcome.
1. Injection Process AI & Closed-Loop Setup
Lead the design, development, and deployment of AI-based closed-loop process control for injection molding machines.
Drive the project rollout for plastic gear and water pump component application, ensuring measurable improvements in capability (Cp/Cpk) and defect reduction.
Integrate real-time process signals, sensor data, and quality feedback to build self-optimizing process loops.
Collaborate with tooling, quality, and production teams to validate AI models on production lines.
2. E2E Injection Process Data Application & JEB Enablement
Architect and implement an end-to-end data pipeline for injection molding process data - from machine/sensor acquisition through storage, analysis, visualization, and decision support.
Build dashboards and reporting tools to visualize process performance, OEE, capability trends, and AI model outputs.
Educate and mentor the JEB team (process engineers, technicians, operators) on how to interpret and act on data in their daily work - shifting from instinct-driven to data-driven decision making.
Create standard operating procedures (SOPs), training materials, and hands-on workshops for sustaining the data culture.
3. Team Capability Building (Software & AI Skills)
Drive technical upskilling of the engineering team across the following software and AI tool stack:
Python - for data analysis, scripting, automation, and ML model development.
SQL - for querying manufacturing databases, process historians, and MES systems.
LLM / RAG (Large Language Models & Retrieval-Augmented Generation) - for building knowledge assistants, troubleshooting guides, and document intelligence tools.
Azure AI Studio - for developing, deploying, and managing AI models in the cloud.
Power BI - for creating interactive process dashboards and real-time visual analytics.
Manufacturing Process Knowledge - deep understanding of injection molding, material science, and process optimization.
Lead at least 1-2 full-cycle AI project deployments into production, managing the end-to-end lifecycle from problem definition, data collection, model training, validation, deployment, and monitoring.
4. Cross-Functional Collaboration & Innovation
Partner with IT, Data Engineering, and OT (Operational Technology) teams to ensure seamless data connectivity between shop floor systems and cloud/analytics platforms.
Identify new opportunities for AI/ML application in manufacturing (e.g., predictive maintenance, defect classification, yield optimization).
Stay current with emerging trends in AI for manufacturing and introduce relevant innovations to the organization.
Document project outcomes, best practices, and lessons learned for organizational knowledge retention.
Bachelor's degree or higher in Mechanical Engineering, Manufacturing Engineering, Computer Science, Data Science, Electrical Engineering, or a related technical field.
Fresh graduate are welcome.
Friendly and stable working environment
Comprehensive on-the-job training, engaging classroom sessions, and an extensive e-learning system
Global exposure with excellent career development opportunities
Free accommodation and shuttle bus provided by company