PROBE AREA ENGINEER

Work with PEE, PIE and Planning team to enable short to mid-term capacity and cycle time planning for the area to meet Business Plan Identify area constraints, establish and implement best known method to resolve them Work with relevant cross functional teams in building the infrastructure and fan out to the shift team to run the area more effectively, i.e manufacturing system deployment, enhancement, and training Drive productivity and quality improvement projects, such as cycle time reduction, RPT improvement, operations simplification, man model optimization, etc Participate in resolving gaps in actual vs modeled performance Set up and maintain automated systems to disposition product Define and streamline business processes at Probe to improve coordination across multiple teams Improve robustness of Probe systems and operations Perform system setup to support new NAND devices at Probe All team members are required to complete their learning items within the stipulated time frame Explore and develop agentic AI approach to plan to performance health detection, analysis, predict, and optimize performance. Maintain close communication and collaboration with production and process collaborators to achieve strategic business objectives, including alignment on digital and AI transformation initiatives. For business process and/or QMS component that one is responsible or accountable for: ensuring the QMS/business process that is effective and conforms to requirements ensuring that the processes are delivering their intended outputs reporting on QMS/business process performance and opportunities for improvement to management ensuring the promotion of internal and external customer focus throughout the organization ensuring the maintenance of the integrity of the QMS/ business process when changes are planned and implemented. ensuring customer requirements are met Bachelors Degree in Engineering Basic understanding of manufacturing concepts (capacity planning, cycle time, operations research, factory physics, production planning/scheduling, etc) Basic understanding of process/equipment knowledge Strong analytical and problem solving skills with the ability to identify and close inefficiency gaps Proficient in Microsoft office skills Independent and self-motivated Ability to multi-task, work efficiently, and complete the assigned tasks within designated timeline Adaptive to change and challenge in high pace manufacturing environment Strong leadership and communication skills Understanding or interest in AI applications in semiconductor manufacturing, such as predictive analytics, automated defect classification, or data visualization is preferred. Proficient in SQL, Python and tableau setup is preferred