engineer, nveg product engineering
2 weeks ago
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.
JR53741 ENGINEER, NVEG PRODUCT ENGINEERING (ADV ANALYTICS)Responsibilities include, but not limited to:
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.Minimum Qualifications:
Bachelor's/Master's in Electrical/Electronic Engineering, Computer Engineering, Computer Science, Data Science. Strong drive and excellent written and verbal communication skills, including ability to effectively communicate complex technical ideas/concepts. Knowledge of Machine Learning/Deep Learning methodology will be an added advantage. Strong analytical and problem-solving skills, with the ability to find creative solutions to difficult problems Effective communication skills in written and spoken English Good multitasking skills and ability to set priorities in a fast moving, dynamic environment Self-motivation and enthusiasm-
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