Senior Engineer, Manufacturing Engineering
On-siteSi Maha Phot, Changwat Prachin Buri, Kingdom of Thailand
Job Summary
Support Manufacturing Engineering team in resolving production capacity issues and assist in productivity and DGR improvement activities through data analysis and process studies. Manage capacity line setup, conversion, scheduling, and production ramp-up while participating in day-to-day output gap analysis and issue resolution. Contribute to OEE/TEEP data collection, cost improvement projects, and capital budget tracking. Develop team processes using AI and Industry 4.0 technologies to enhance efficiency. This Early Career role includes structured onboarding and mentorship for fresh graduates or those with 0–2 years of experience in Manufacturing or Industrial Engineering.
Required Qualifications
- Currently pursuing or recently completed Master's degree in Manufacturing Engineering, Industrial Engineering, Mechanical Engineering, or equivalent experience
- Fundamental understanding of manufacturing processes, production flow, and capacity concepts gained through coursework or academic projects
- Basic knowledge of productivity improvement and industrial engineering principles (e.g., line balancing, cycle time, throughput)
- Introductory understanding of OEE / equipment efficiency metrics
- Ability to support production capacity and output gap analysis under guidance
- Basic awareness of manufacturing cost concepts and willingness to participate in cost improvement activities
- Willingness to learn and assist with capital equipment justification, purchase requests, and order tracking
- Strong interest in applying AI, Industry 4.0, and digital technologies to improve manufacturing efficiency
Desired Qualifications
- Internship, co‐op, or project experience in a manufacturing or production environment
- Exposure to line setup, line conversion, or production ramp‐up through internships or university projects
- Coursework or project experience in Lean Manufacturing, Six Sigma, or Continuous Improvement
- Experience using data analysis tools (Excel, dashboards, basic simulations) for capacity or productivity analysis
- Academic or project exposure to AI, data analytics, automation, smart manufacturing, or digital factory concepts
- Familiarity with manufacturing KPIs such as output, yield, OEE, or cycle time
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