Lead Product Engineer

Job Role: Lead Product Engineer

Work Location: Austin, USA

Job Description:

As a Lead 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.