Manufacturing Engineer (Machine Learning)

Location: Bayan Lepas, Malaysia; onsite only

Company

hirify.global is an embedded semiconductor solution provider developing technology for automotive, industrial, infrastructure, and IoT applications.

What you will do

• Analyze production data to identify yield, cycle-time, cost, and process-performance improvement opportunities.
• Plan and execute Lean, Six Sigma, TPM, DOE, and Operational Excellence projects through implementation and results validation.
• Build and deploy machine learning models for yield prediction, computer-vision defect detection, and anomaly detection in partnership with Data Science and IT.
• Develop real-time dashboards, automated reports, and data pipelines for process monitoring.
• Support Industry 4.0 initiatives, including MES integration, IIoT sensors, robotics, and automated material handling.
• Investigate quality excursions, maintain SPC systems, support NPI qualification, and implement corrective and preventive actions.

Requirements

• Bachelor’s degree in Industrial, Manufacturing, Electrical, Mechanical, Software Engineering, Computer Science, or a related technical field.
• 2–5 years of experience in manufacturing, process, or industrial engineering, preferably in semiconductor or electronics manufacturing.
• Hands-on experience with Lean Six Sigma tools, including DOE, root-cause analysis, and value stream mapping.
• Practical experience building or deploying machine learning models using Python and common machine learning libraries.
• Working knowledge of SPC, Cpk analysis, and data visualization, with strong data analysis skills using Python, SQL, Minitab, JMP, Excel, or Power BI.
• Comfort working directly on the shop floor with equipment, operators, and production data.

Culture & Benefits

• Regular permanent employment with a competitive benefits package alongside the salary.
• Collaborative, transparent, agile, global, innovative, and entrepreneurial working culture.
• Opportunity to work with a global semiconductor team operating across more than 30 countries.
• Work focused on automotive, industrial, infrastructure, and IoT technologies.