Job Title

Job Description: As a Lead/Architect Product Engineer at LTSCT, you own the product engineering and will interface with design, foundry, test, reliability, OSAT and FA to debug and solve product/process related issues in pre-production and production phases. You will be responsible for process improvements to reduce production costs and increase yields. Product Engineer will manage new product introduction and production support engineering for a specific product or group of products after they have been transferred from design to fabrication until production. Responsibilities include: Coordinate with all internal stakeholders for product design, package design, fabrication, package assembly, test and qualification for enabling the product for volume manufacturing Active involvement in pre-silicon test program, hardware development and post silicon stage for timely delivery of product at the target cost, quality and target volume. Define the Risk Assessment and Mitigation plan in every critical stage of the project using FMEA Point of contact for all the issue resolution during the whole project cycle within LTSCT team and partners. Drive technically the teams responsible for product releases, Fab & OSAT partners for high volume manufacturing on ATE platform for Automotive, Industrial and Energy products. Perform vigorous signoff for new test systems (program/hardware) per manufacturing requirements. Perform the correlation study, analysis and release of Test program for manufacturing. Support daily production issues at test floor for wafer probe and Final Package Test. This includes low yield analysis and disposition, setup failure debug/analysis and resolution (both hardware and software). Provide detailed analytical study on above issues in collaboration with design, process, reliability, test to narrow down root cause and solve product issues in terms of yield, stability and quality. Engage in productivity improvement projects, including yield improvement, test time reduction, test insertion removal etc. Develop and own yield roadmap, dashboards, and reports to track yield performance and provide insights to stakeholders. Provide support for IC Reliability, Online Reliability Monitoring, Failure Analysis and RMA Handling. Lead and support introduction of new tool/equipment/test processes to manufacturing for new product releases, leading the entire qualification and change management approval. Engage & manage OSAT in early production stage. Your Profile You are best equipped for this task if you have: Bachelor’s or Master’s degree in Electrical and Electronic Engineering with preferred more than 10 years of relevant experience in Semiconductor Industry. Good understanding of the complete life cycle of Semiconductor IC development and production Proven expertise with process technology, knowledge of WAT, WS, CP, Final Test data analysis and correlation with Test Yield. Strong background on yield detractor root causes by product design margin, fab manufacturing excursions or variation, test margin/instability & operational inefficiency. Knowledge of semiconductor device physics, Analog/Mixed signal and Digital test concepts, ATE Test program, Device characterization and Test debug. Knowledge of FMEA derived Semiconductor IC Product Qualification Plan (JEDEC/AECQ-100/101), IC Reliability, Failure Analysis and RMA Handling. Knowledge on DFT, DFM, DFR and DFFA Familiarity with industry-standard yield analysis tools, such as PDF Exensio, JMP, Spotfire etc. and in generating reports with a data driven approach. Good knowledge of general semiconductor industry process quality control system and statistical analysis methodology: SPC charts review, Cp, Cpk improvement, GR&R etc. Excellent analytical, problem-solving, and communication skills, with the ability to work effectively in a cross-functional team environment. Leadership skills with a track record of managing multi-disciplinary and multi-cultural teams. Candidates with experience in cross-functional collaboration and exposure to international teams is a must Knowledge of machine learning or artificial intelligence techniques applied to yield enhancement is a plus. Independent, resourceful and takes initiative. Good Command of English.