Snr/Product Engineer
2 weeks ago
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.
Requirements:
- Bachelor's/Master's in Electrical/Electronic Engineering with at least 5 years of experienc in Yield anlaysis and Data processing.
- Experience in SQL automation scripting and data analysis tools such as JMP for data processing.
- Experience in driving product yield improvement and product monitoring dashboard automation.
- 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
Analytical Skills
Quality Assurance
Problem Solving
Electrical
Reliability
Research and Development
Characterization
Communication Skills
Flash
Simulations
Verilog
Manufacturing
Silicon
CAD
Failure Analysis
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