AI Infrastructure Applications Engineer Intern

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