About the role
AI summarisedThe Probe Area Engineer is responsible for optimizing manufacturing operations in the probe area by driving productivity and quality improvements, managing capacity and cycle time planning, resolving operational constraints, and supporting new device introductions. This role involves collaborating with cross-functional teams to enhance manufacturing systems, streamline business processes, and ensure QMS compliance. The engineer also leads initiatives involving AI and data analytics to predict and optimize performance, while maintaining alignment with business objectives and digital transformation goals.
IDMOnsiteFront End
Key Responsibilities
- 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
- 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.
- Ensuring the QMS/business process that is effective and conforms to requirements
Requirements
- 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
- Interest in and knowledge of the semiconductor industry and Micron is preferred