Process Engineering Manager

Job Description

Renesas is looking for an experienced Process Engineering Manager to lead the site’s 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 site’s 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

• Bachelor’s degree in Industrial, Manufacturing, Electrical & Electronics, Mechanical, or Chemical Engineering, or a related technical field. Master’s 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 21,000 engineers and problem solvers in more than 30 countries, we offer the opportunity to work on world‑leading 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.

• Employment Type: Regular (PERM)
• Remote Work Available: No