Quality Engineer - FEOL

About the role

Applied Materials, a global leader in materials science and engineering solutions for semiconductors and advanced displays, is hiring a Quality Engineer for its FEOL function in Singapore. The role oversees manufacturing quality, works with Manufacturing and Engineering teams, and requires the ability to travel on short notice.

Key responsibilities

• Oversee manufacturing processes to ensure adherence to quality standards and specifications.
• Develop and strengthen quality assurance systems that improve product quality, process capability and manufacturing consistency.
• Set quality objectives, monitor KPIs and drive improvements in customer quality, defect reduction and process performance.
• Partner with Manufacturing and Engineering teams to embed quality into production and new technology implementation.
• Foster a prevention-based quality culture focused on risk anticipation, process capability, operational discipline and continuous learning.
• Govern manufacturing quality risk through PFMEA, Control Plans, change management, MRB, PCN and quality reviews.
• Proactively identify, investigate, mitigate and monitor quality risks, non-conformities and systemic issues, and drive recurrence prevention.
• Use statistical methods such as Statistical Process Control and Design of Experiments to interpret data, identify trends and drive yield and performance improvements.
• Work with process, integration and reliability teams and internal and external customers to meet product specifications and quality standards.

Required profile

• Degree in Electrical Engineering, Chemical Engineering, Materials Science or a related field.
• At least 5 years of work experience.
• More than 3 years of proven in-process quality control experience in a high-volume manufacturing environment.
• Strong understanding of nanotechnology processes, including lithography, etch, deposition and metrology.
• Preferred: experience in FEOL optics or semiconductor fabrication.
• Able to travel on short notice; relocation is not eligible.

Required skills

• Statistical data analysis and process optimization and control techniques (Design of Experiments, SPC, JMP).
• PFMEA, Control Plans, MRB and PCN knowledge.