Senior Staff Engineer, Digital Twin & Process Control

Infineon Technologies (Malaysia) Sdn Bhd; Malacca City; On-site; MYR 240,000 - 360,000; Full time

Job summary

Infineon Technologies (Malaysia) Sdn Bhd is seeking a Senior Staff Engineer for Digital Twin Equipment & Process to lead development of advanced manufacturing solutions. You will drive Digital Twin and APC programs, analyze data, and implement predictive and self-healing capabilities within a global, cross-functional team.

The role focuses on integrating Digital Twin, APC, FDC, and analytics into MES and automation platforms to improve yield, throughput, and equipment effectiveness while

Qualifications

• Bachelor's or Master's Degree in Electrical/Mechanical/Mechatronics, Automation, or related field.
• 8+ years of experience in semiconductor manufacturing, digital manufacturing, process engineering, or APC implementations.
• Strong understanding of data analytics, AI/ML applications, and continuous improvement methods such as Lean Six Sigma.

Responsibilities

• Lead the development and deployment of Digital Twin, APC, and analytics solutions to boost manufacturing performance.
• Leverage equipment, process, and quality data to drive data-driven decisions.
• Design predictive, adaptive, and closed-loop control strategies using APC, Digital Twins, FDC, and analytics.
• Collaborate with cross-functional teams to deliver scalable smart manufacturing solutions.

Skills

Digital Twin

APC

Data analytics

Python

SQL

Lean Six Sigma

Cross-functional teams

Education

Electrical/Mechanical/Mechatronics engineering

Tools

KNIME

MATLAB

SECS/GEM

Job description

Infineon Technologies (Malaysia) Sdn Bhd is seeking a Senior Staff Engineer for Digital Twin Equipment & Process to lead development of advanced manufacturing solutions. You will drive Digital Twin and APC programs, analyze data, and implement predictive and self-healing capabilities within a global, cross-functional team.

The role focuses on integrating Digital Twin, APC, FDC, and analytics into MES and automation platforms to improve yield, throughput, and equipment effectiveness while