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engineering opportunity

AI Infrastructure Applications Engineer Intern

The intern will support Velocity EDA-to-ATE conversion workflows and contribute to the development of automation scripts for semiconductor applications. They will also collaborate with engineering teams on AI-assisted workflows, including pattern diagnostics, log analysis, and data interpretation.

San Jose, California, United StatesonsiteINTERN,FULL_TIME

Posted

About the role

What will you do at Advantest?

About the Role

We are seeking a highly motivated engineer to learn and support our Velocity

EDA-to-ATE software platform and leverage AI-based tools to connect Velocity

outputs with a variety of engineering tools and workflows.

This is a unique opportunity to gain hands-on experience across the

semiconductor lifecycle, including design, validation, and test, while working

with advanced automation technologies used in modern chip development.

As part of the role, you will be exposed to automated test conversion flows

spanning design, DFT, simulation, and production ATE environments. You will

collaborate closely with experienced Applications Engineers and internal

development teams to support the deployment and enhancement of automation

methodologies that improve efficiency and accelerate time-to-market.

Key Responsibilities

  • * Assist in supporting Velocity EDA-to-ATE conversion workflows for
  • semiconductor applications
  • * Participate in conversion activities involving formats such as STIL, WGL,
  • EVCD, and related environments
  • * Support debugging and analysis of conversion, timing, and pattern-related
  • issues under guidance
  • * Contribute to the development of automation scripts and utilities using
  • Python, Java, or similar technologies
  • * Collaborate with internal engineering teams to gain exposure to DFT,
  • simulation, and ATE production workflows
  • * Assist in log analysis, data processing, and structured data interpretation
  • * Support validation and regression testing of conversion flows
  • * Participate in AI-assisted engineering workflows, including:
  • * Pattern debug and diagnostics
  • * Log parsing and data analysis
  • * Automation and script generation tasks
  • * Document workflows, findings, and best practices to support knowledge
  • sharing
  • * Engage in team discussions and contribute to technical problem-solving
  • activities
  • What You’ll Gain
  • * Practical experience with semiconductor test and conversion workflows in a
  • production-oriented environment
  • * Exposure to industry-standard tools such as Velocity, VTRAN, and ATE
  • platforms (e.g., Advantest V93000)
  • * Mentorship from experienced Applications and Software Engineering
  • professionals
  • * Insight into AI-driven automation and modern semiconductor development
  • practices
  • * Opportunity to contribute to impactful engineering solutions used by global
  • semiconductor customers

Minimum Qualifications

  • * Currently pursuing a bachelor’s or master’s degree in electrical engineering,
  • computer engineering, computer science, or a related discipline
  • * Foundational understanding of digital design or semiconductor fundamentals
  • * Experience or familiarity with programming or scripting languages such as
  • Python, Java, or C++
  • * Experience in AI/ML applications in engineering workflows
  • * Strong analytical and problem-solving abilities
  • * Effective communication and collaboration skills
  • * Demonstrated interest in automation, semiconductors, or test engineering
  • * Willingness to learn and contribute in a dynamic engineering environment

Preferred Qualifications

  • * Exposure to Design-for-Test (DFT) concepts such as scan or ATPG
  • * Familiarity with EDA tools or semiconductor workflows
  • * Basic knowledge of test pattern formats (e.g., STIL, WGL)
  • * Experience working in Linux/Unix environments

Which skills does this role require?

PythonJavaC++Semiconductor FundamentalsDigital DesignAutomationData AnalysisLog ParsingDebuggingAI InfrastructureVelocityATEEVCDAdvantest V93000Machine LearningRegression TestingVTRANSoftware EngineeringApplications EngineeringChip DevelopmentValidationTest EngineeringPattern Diagnostics

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