Job Description

As an Application Engineer for the V93000 SoC ATE system, you will support our global customer base in developing, optimizing, and troubleshooting semiconductor test programs while also playing a key role in enabling AI/LLM capabilities within our software ecosystem This hybrid role combines deep semiconductor test expertise with modern AI engineering: developing test methodologies, supporting customer projects, and collaborating on integration of LLM-driven tools that enhance productivity, test automation, and engineering workflows across SmarTest 8 and related platforms.

You will bridge the worlds of ATE application engineering and AI-assisted engineering, contributing to next-generation smart tooling that improves test quality, reduces debug time, and unlocks intelligent automation for semiconductor development and production.

Key Responsibilities:

• Provide application development support for V93000 SoC ATE systems, including test program creation, debug, and optimization in context of AI project
• Communicate with customers to understand requirements and ensure successful delivery
• Collaborate with global field engineers, R&D, and application development teams
• Support the integration of AI capabilities into SmarTest 8 and related test development flows
• Collaborate with R&D on the design and validation of LLM-assisted engineering tools, including code generation, error resolution, and automated test documentation
• Assist in dataset preparation, data extraction, and domain-specific curation for LLMs
• Contribute to the evaluation of AI features using semiconductor test scenarios (test programs, debug logs, parametric data)
• Work with Java/C++ and Eclipse-based environments to integrate AI components into existing toolchains
• Provide feedback from real customer use-cases to guide improvement of AI-enabled features
• Help ensure AI tools meet requirements for correctness, robustness, latency, and usability within semiconductor test workflows
• Support internal testing of RAG pipelines, embeddings, and model behaviors in the context of V93000 workflows

Qualifications

• University degree in Electronic Engineering, Electrical Engineering, Computer Science, or related field
• 3–5 years of relevant experience in semiconductor test engineering on ATE platforms (digital, mixed-signal, or RF)
• Hands-on experience developing and debugging test programs on Advantest V93000 / SmarTest 8
• Experience with Java programming; familiarity with C++ is beneficial
• Basic knowledge of Linux environments and command-line tools
• Strong troubleshooting ability and methodical problem-solving mindset
• Good communication and presentation skills for internal and customer-facing activities
• Experience with or interest in AI/ML workflows, NLP concepts, or LLM-based tools (training, fine-tuning, prompt engineering, or evaluation)
• Ability to work independently and as part of a global project team
• Fluent English (mandatory); German is a plus
• Willingness to travel as needed