Manufacturing Quality and Reliability Engineer

Intel Intel · Semiconductors · Chengdu, China

This role focuses on manufacturing quality and reliability engineering, ensuring products meet high standards. It involves overseeing inspection and testing, conducting quality assessments, developing performance indicators, driving process improvements, and managing excursions. A key responsibility is analyzing data using statistics and machine learning to identify insights and disposition products. The role requires expertise in reliability fundamentals, semiconductor physics, and data analysis, with a preference for experience in leading quality improvement initiatives and communicating with diverse stakeholders.

What you'd actually do

  1. Specify and oversee inspection and testing mechanisms to ensure compliance with quality standards for products and production equipment.
  2. Conduct quality assessments and audits, evaluating materials, processes, and techniques used in manufacturing.
  3. Develop and monitor health and performance indicators for product quality and reliability to guide optimization efforts.
  4. Drive continuous process improvement initiatives and foster a quality culture mindset across factories.
  5. Analyze structured and unstructured data using statistics and machine learning to identify insights and determine the disposition of products and systems that do not meet specifications.

Skills

Required

  • Bachelor or Master degree in engineering or a related technical field.
  • Technical expertise in failure modes analysis and group problem-solving methodologies.
  • Proficient written and oral English
  • Proficiency in reliability fundamentals, reliability statistics, and modeling and measurement techniques
  • Strong understanding of semiconductor device physics and reliability verification methods.
  • Skilled in data analysis, machine learning applications, and risk assessment processes.

Nice to have

  • Experience leading cross-functional teams in quality improvement initiatives.
  • Proven ability to communicate effectively with diverse stakeholders, including engineers, suppliers, and customers.
  • Demonstrated disciplined execution of complex projects or manufacturing ramps.
  • Track record of fostering a culture of collaboration and continuous improvement.
  • Commitment to driving innovation and delivering impactful results.

What the JD emphasized

  • Skilled in data analysis, machine learning applications, and risk assessment processes.

Other signals

  • Analyze structured and unstructured data using statistics and machine learning to identify insights and determine the disposition of products and systems that do not meet specifications.
  • Skilled in data analysis, machine learning applications, and risk assessment processes.