Process Engineering Manager

Renesas is looking for an experienced Process Engineering Manager to lead the sites Operational Excellence and Automation agenda in Penang. This role owns process performance across manufacturing lines including yield cycle time and cost while driving the automation and digitalization roadmap that shifts the site from manual reactive operations toward data-driven self-correcting processes. 

The Process Engineering Manager sits at the intersection of process control continuous improvement and technology deployment building the business case for automation investment and leading the engineering team that delivers sustains and scales these solutions across the site.

Key Responsibilities:

• Lead the process engineering team driving yield improvement cycle time reduction and cost-per-unit optimization across assigned manufacturing lines.
• Own the sites Operational Excellence roadmap including Lean Six Sigma and TPM setting targets and tracking OEE first-pass yield and scrap reduction.
• Drive the automation strategy by identifying justifying and implementing automation and robotics projects that reduce manual intervention and improve process consistency. 
• Lead in-house development of process engineering systems and tools including data pipelines real-time dashboards and automated reporting for faster and more reliable decision-making. 
• Champion AI and machine learning solution development for manufacturing including ML-based yield prediction computer-vision defect detection and anomaly detection partnering with Data Science and IT teams to deploy solutions into production. 
• Own the roadmap for embedding AI/ML into process control through adaptive SPC limits predictive quality alerts and early excursion detection to enable automated model-driven decision-making.
• Partner with software and IT teams to architect scalable data infrastructure including MES and data lake integration supporting automation analytics and AI/ML initiatives.
• Lead Industry 4.0 and smart manufacturing initiatives including MES integration real-time SPC predictive analytics and IIoT sensor deployment. 
• Collaborate with Equipment Maintenance Quality and Manufacturing teams to resolve yield and quality excursions using structured problem-solving methodologies such as 8D DMAIC and FMEA. 
• Own process qualification and control plans for new product introduction (NPI) and process change management. 
• Build business cases including ROI and payback analysis for automation system development and AI/ML investments while managing the process engineering CAPEX budget. 
• Establish and maintain Statistical Process Control (SPC) systems and process capability (Cpk) targets across critical process steps. 
• Lead coach and develop a team of process engineers while building data science software and AI/ML literacy within the organization and strengthening succession readiness.
• Benchmark industry best practices and lead cross-site knowledge sharing on Operational Excellence automation and AI/ML applications in manufacturing. 
• Present Operational Excellence automation and AI/ML roadmap progress to site and regional leadership.

Qualifications :

• Bachelors degree in Industrial Manufacturing Electrical & Electronics Mechanical or Chemical Engineering or a related technical field. Masters degree is a plus.
• 8 years of process engineering experience in semiconductor or electronics manufacturing with at least 3 years in a managerial capacity.
• Proven track record leading Lean Six Sigma or Operational Excellence programs with measurable yield cost or throughput improvements. 
• Experience leading automation or Industry 4.0 projects from business case development through implementation and sustained adoption. 
• Strong SPC DOE and process capability (Cpk) analysis skills. 
• Experience managing a process engineering or automation CAPEX budget.
• Working knowledge of quality systems such as ISO 9001 IATF 16949 or equivalent as they apply to process control and change management.

Preferred Skills: 

• Six Sigma Black Belt or Lean Master certification.
• Experience with robotics cobots or Automated Material Handling Systems (AMHS) in a manufacturing environment. 
• Familiarity with MES SCADA or IIoT platforms for real-time process monitoring and control. 
• Data analytics or programming skills using Python SQL Minitab or JMP for advanced process and yield analysis.
• Exposure to machine learning frameworks such as scikit-learn or TensorFlow with experience deploying models in manufacturing environments.
• Experience leading organizational change management for new technology or process adoption

Additional Information :

Renesas is an embedded semiconductor solution provider driven by its Purpose To Make Our Lives Easier. With a global team of over 21000 engineers and problem solvers in more than 30 countries we offer the opportunity to work on worldleading technology for Automotive Industrial Infrastructure and IoT shaping a safer healthier greener and smarter future.

At Renesas TAGIE is our culture grounded in being Transparent Agile Global Innovative and Entrepreneurial. It shapes how we work grow and deliver on our purpose together. This collaborative spirit and mindset drive our semiconductor technology to transform industries and impact millions of lives.

We believe in rewarding our employees with a competitive benefits package alongside their salary. More information will be provided during the hiring process.

Are you ready to join our team and shape the future with us

Renesas Electronics is an equal opportunity and affirmative action employer committed to supporting diversity and fostering a work environment free of discrimination on the basis of sex race religion national origin gender gender identity gender expression age sexual orientation military status veteran status or any other basis protected by law. For more information please read our Diversity & Inclusion Statement.

Remote Work :

No

Employment Type :

Full-time