Electrical Engineer Jobs

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About The Position

The Yield Enhancement Electrical Failure Analysis Engineer performs investigative electrical failure analysis to identify, categorize, and resolve defect issues affecting yield. The role combines hands-on electrical characterization, advanced data analytics, automation, and AI-enabled engineering workflows to accelerate defect detection, root cause identification, and yield improvement. The engineer monitors manufacturing performance, prioritizes yield investigations, and delivers data-driven insights and clear reporting to support business decisions and continuous improvement. The position works with Fab and Yield Engineering teams and partners across Design, Process Integration, Product Engineering, Test, Manufacturing, and Data Science. It supports yield and reliability investigations, new product introduction, qualification, technology transfers, and improvements to product quality and engineering productivity. The role also involves technical communication, documentation, knowledge sharing, and mentoring.

Requirements

  • Bachelor's or master's degree in Electrical Engineering, Computer Engineering, Materials Science, Computer Science, Data Science, or Chemical Engineering.
  • Ability to apply knowledge of semiconductor devices, process integration, memory architecture, and device operation to analyze electrical failures and yield issues.
  • Ability to perform electrical and failure analysis as defined by area skill guidelines.
  • Experience conducting advanced data analysis, statistical evaluation, and data visualization to support yield investigations and failure-analysis results.
  • Proficiency with data analytics, scripting, automation, or programming tools such as Python, SQL, JMP, Power BI, Tableau, or equivalent.
  • Ability to use AI tools, large language models, and automation technologies to improve data processing, engineering productivity, investigation efficiency, and technical reporting.
  • Ability to summarize investigation findings, including potential root cause and recommended actions, in a concise and technically sound report.
  • Ability to operate laboratory equipment safely and perform required tasks and basic troubleshooting.

Nice To Haves

  • Experience applying AI, machine learning, predictive analytics, or large language models to engineering, failure analysis, manufacturing, or yield-improvement workflows.
  • Experience developing automated data-processing pipelines, dashboards, engineering applications, or workflow-automation solutions.
  • Experience mentoring or assisting failure-analysis technicians during yield investigations.
  • Familiarity with Merlin/Raptor tester platforms, emission tools, MPI probe stations, nanoprobe tools, and associated data-analysis environments.
  • Experience maintaining technical knowledge of semiconductor device structure, operation, and failure mechanisms for current and future technologies.
  • Demonstrated participation in digital transformation, AI adoption, continuous-improvement initiatives, or cross-functional technical projects.
  • Willingness to evaluate emerging AI technologies and drive adoption of innovative engineering solutions that improve team effectiveness and productivity.

Responsibilities

  • Perform electrical and failure analysis according to area skill guidelines, and summarize findings with clear, data-driven reporting and AI-assisted documentation tools.
  • Operate and support laboratory equipment while following safety guidelines and supporting department and company objectives.
  • Drive root-cause investigations by correlating electrical test data, failure-analysis results, process information, manufacturing history, and AI-generated insights; identify yield detractors and recommend corrective actions.
  • Develop and maintain yield-monitoring methodologies, screening strategies, defect-classification systems, and AI-assisted detection models.
  • Partner with Design, Process Integration, Product Engineering, Test, Manufacturing, and Data Science teams to resolve yield and reliability issues and improve product quality.
  • Develop, automate, and maintain data-analysis tools, dashboards, reporting systems, and AI-powered workflows to improve investigation efficiency and reduce manual data processing.
  • Apply AI, machine learning, statistical methods, and advanced analytics to defect identification, yield trending, anomaly detection, predictive analysis, and root-cause determination.
  • Use generative AI and knowledge-management tools to support technical reviews, investigation planning, report generation, and information retrieval.
  • Lead technical reviews and communicate investigation results, risks, recommendations, and data-driven insights to cross-functional stakeholders and management.
  • Create and maintain technical documentation, best practices, training materials, AI prompt libraries, and knowledge-sharing resources.
  • Evaluate and implement electrical-characterization and debug methodologies, automation solutions, and AI-enabled failure-analysis techniques.
  • Support new product introduction, qualification activities, and technology transfers with yield analysis, failure-investigation expertise, and data-driven risk assessments.
  • Identify opportunities for process improvement, cost reduction, cycle-time reduction, and productivity enhancement through automation, AI adoption, and workflow optimization.
  • Provide technical mentorship and training to engineers and technicians on semiconductor device operation, failure mechanisms, data analytics, AI-assisted engineering tools, and debug methodologies.
  • Identify, evaluate, and implement emerging technologies that improve engineering productivity, technical insight generation, and decision-making.
  • Manage and prioritize multiple investigations while ensuring timely communication of critical findings and business-impacting issues.

Benefits

  • Choice of medical plans
  • Choice of dental plans
  • Choice of vision plans
  • Income-protection benefit programs for illness or injury
  • Paid family leave
  • Paid time off
  • Paid holidays

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