ENGINEER, NVEG PRODUCT ENGINEERING (ADV ANALYTICS)
at Micron
Singapore, Southeast, Singapore -
Start Date | Expiry Date | Salary | Posted On | Experience | Skills | Telecommute | Sponsor Visa |
---|---|---|---|---|---|---|---|
Immediate | 03 Aug, 2024 | Not Specified | 05 May, 2024 | N/A | Communication Skills,Data Science,English,Computer Engineering,Computer Science | No | No |
Required Visa Status:
Citizen | GC |
US Citizen | Student Visa |
H1B | CPT |
OPT | H4 Spouse of H1B |
GC Green Card |
Employment Type:
Full Time | Part Time |
Permanent | Independent - 1099 |
Contract – W2 | C2H Independent |
C2H W2 | Contract – Corp 2 Corp |
Contract to Hire – Corp 2 Corp |
Description:
OUR VISION IS TO TRANSFORM HOW THE WORLD USES INFORMATION TO ENRICH LIFE FOR ALL.
Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing.
Responsibilities:
- Responsible for in-depth data analysis to look for sighting that is detected from reliability testing on certain cell marginality.
- To work closely with cross functional team to drive for cause, cell mechanism understandings and mitigation plan (device and process) when sightings of cell marginality are noted.
- Look into volume reliability data to probe data correlation to look for signals for cell metrics/kill limit recommendation to guardband intrinsic reliability capability.
- Enable proactive methodology for cell reliability analytic study on both die and wafer level assessment using advanced product-dispo techniques.
- Enable proactive methodology for defectivity (DPM) reduction at wafer level using advanced product-dispo techniques.
- Develop state-of-art and advanced algorithms, encompassing advanced models to boost and enhance data-mining and pattern recognition for quality and yield improvement.
- Work with Product/Fab/Engineering teams on product issues (yield/cell/qualification/defectivity/RMA/deviations) in problem analysis, data-mining and modeling, to provide optimal disposition solution.
- Implement and validate product-dispo solution with minimal yield impact and to track effectiveness of solutions.
- Develop understanding of test flows and product-dispo framework and make use of big Data to highlight strength and weaknesses in production process and improve quality of material produced with lower cost and faster cycle time
REQUIREMENT SUMMARY
Min:N/AMax:5.0 year(s)
Information Technology/IT
IT Software - Other
Software Engineering
Graduate
Proficient
1
Singapore, Singapore