INTERNSHIP DETAILS

Application Engineering Intern

CompanyAdvantest
LocationRichardson
Work ModeOn Site
PostedApril 16, 2026
Internship Information
Core Responsibilities
The intern will develop and debug test programs while integrating AI tools to automate repetitive engineering tasks. They will also collaborate with cross-functional teams to build dashboards and implement intelligent automation solutions for semiconductor validation.
Internship Type
full time
Company Size
3818
Visa Sponsorship
No
Language
English
Working Hours
40 hours
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About The Company
Advantest (TSE: 6857) is the leading manufacturer of automatic test and measurement equipment used in the design and production of semiconductors for applications including 5G communications, the Internet of Things (IoT), autonomous vehicles, high performance computing (HPC) including artificial intelligence (AI) and machine learning, and more. Its leading-edge systems and products are integrated into the most advanced semiconductor production lines in the world. The company also conducts R&D to address emerging testing challenges and applications; develops advanced test-interface solutions for wafer sort and final test; produces scanning electron microscopes essential to photomask manufacturing; and offers system-level test solutions and other test-related accessories. Founded in Tokyo in 1954, Advantest is a global company with facilities around the world and an international commitment to sustainable practices and social responsibility. More information is available at www.advantest.com.
About the Role

About the Role

We are looking for a motivated and technically curious intern to join our Application Engineering team. In this role, the intern will have the opportunity to learn and grow their analytical and quantitative skills while doing test program debugging and development. They will also work on generating templates that would allow AI integration for automated test program generation.

What You Will Do

  • Use large language models (LLMs) and AI coding assistants to rapidly prototype scripts, data pipelines, and analysis tools that support test program development.
  • Automate repetitive engineering tasks such as test data extraction, result parsing, yield analysis, and report generation using AI-augmented toolchains.
  • Collaborate with test, design, and product engineers to identify manual bottlenecks and implement intelligent automation solutions.
  • Build and maintain dashboards or internal tools that provide real-time visibility into test metrics, yield trends, and program health.
  • Evaluate and integrate emerging AI tools and APIs into existing engineering workflows to improve team productivity.
  • Document processes, automation recipes, and best practices to enable team-wide adoption.

Why This Role Matters

AI chips are pushing the boundaries of performance and complexity, and the engineering workflows that bring them to life must evolve just as fast. By embedding AI-driven automation directly into our test and validation pipeline, you will help reduce time-to-market, improve yield, and enable the team to focus on high-value engineering challenges instead of repetitive manual tasks. Your work will have a tangible impact on products that power the future of artificial intelligence.

What You Will Gain

  • Hands-on experience applying AI to real-world semiconductor engineering problems.
  • Deep exposure to the full silicon lifecycle — from design validation through high-volume manufacturing.
  • Mentorship from experienced test and product engineers at the forefront of AI chip development.
  • A portfolio of automation projects you can showcase to future employers.
  • The opportunity to shape how a world-class engineering team integrates AI into daily operations.

 

Qualifications

What We Are Looking For

  • Currently pursuing a B.S. or M.S. in Electrical Engineering, Computer Engineering, Computer Science, or a related field.
  • Strong programming skills in Python; familiarity with scripting, data manipulation (Pandas, NumPy), and API integration.
  • Demonstrated interest in or hands-on experience with AI/ML tools, LLMs, prompt engineering, or AI-assisted development (e.g., Claude, ChatGPT, Copilot).
  • Exposure to any of the following is a plus: semiconductor test (ATE), silicon validation, test program development, or hardware debug.
  • Ability to learn quickly, work independently, and communicate technical concepts clearly to cross-functional teams.
Key Skills
PythonData manipulationPandasNumPyAPI integrationLarge language modelsPrompt engineeringAI coding assistantsTest program debuggingAutomationData extractionYield analysisReport generationHardware debugSilicon validationSemiconductor test
Categories
EngineeringTechnologySoftwareData & AnalyticsManufacturing
Benefits
MentorshipHands-on experiencePortfolio development