Job Description

As an R&D Engineer, you will work on cutting-edge AI and machine learning solutions, with a focus on Large Language Models (LLMs), to enhance semiconductor testing and electrotechnical systems. You will design, implement, and optimize end-to-end AI pipelines, integrating LLM-driven tools into testing workflows and contributing to the development of advanced semiconductor test automation.

Key Responsibilities:

• Design, implement, test, and continuously optimize end-to-end RAG (retrieval-augmented generation) pipelines, including data parsing, ingestion, prompt engineering, and chunking strategies
• Integrate AI components with existing systems, requiring experience in Java or C++ and familiarity with Eclipse
• Curate and develop high-quality datasets, including synthetic data generation for robust training and evaluation of LLMs
• Preprocess datasets, fine-tune open-source LLMs (e.g., LLaMA, Mistral), and integrate RAG systems into semiconductor testing pipelines
• Rigorously evaluate LLM applications on correctness, latency, and hallucination metrics
• Assist in deploying LLM-based applications, analyze user feedback, and contribute to iterative improvements
• Write clean, maintainable, and testable code following software engineering best practices
• Collaborate with cross-functional agile teams to translate customer requirements into prototype solutions, with opportunities to lead smaller sub-projects
• Analyze semiconductor testing data (parametric measurements, yield logs) using statistical methods and visualization tools
• Contribute to MLOps workflows for model training, evaluation, and deployment using Python frameworks (PyTorch, Hugging Face) and cloud platforms (AWS/Azure)
• Integrate AI components with existing systems, requiring experience in Java or C++ and familiarity with Eclipse
• Work in Linux environments and handle command-line tools, scripting, and system operations

Qualifications

• University degree in Data Science, Computer Science, Electrical Engineering, or a related field (Master’s preferred, Bachelor’s with 3+ years’ experience accepted)
• Experience with Advantest V93000 test systems / SmarTest 8
• Experience in Eclipse Plugin development
• 1–3 years of hands-on experience in machine learning, including coursework or practical work with NLP or LLMs
• Proficiency in Python for data analysis (Pandas, NumPy) and ML model development (scikit-learn, PyTorch)
• Experience programming in Java or C++
• Strong understanding of Linux, including command-line usage, system navigation, and scripting
• Familiarity with LLM concepts: transformer architectures, prompt engineering, text generation techniques
• Foundational knowledge of MLOps practices: version control (Git/DVC), containerization (Docker), and cloud deployment
• Experience with Jupyter notebooks / VS Code
• Strong communication skills in English; ability to document technical work clearly
• Exposure to semiconductor testing data or industrial IoT datasets
• Experience with RAG systems, LLM fine-tuning workflows (LoRA, QLoRA)
• Familiarity with integrating AI components into existing test platform codebases
• Elementary German proficiency