R&D Engineer - Semiconductor Testing & AI Integration (m/f/d)
07.12.2025
Advantest Europe GmbH
Munich
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R&D Engineer - Semiconductor Testing & AI Integration (m/f/d)
Munich
Aktualität: 07.12.2025
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07.12.2025, Advantest Europe GmbH
Munich
R&D Engineer - Semiconductor Testing & AI Integration (m/f/d)
Aufgaben:
As a Data Scientist (m/f/d), you will collaborate with senior team members to develop and deploy machine learning solutions, with a focus on Large Language Models (LLMs), for semiconductor testing and electrotechnical systems
Assist in designing and implementing LLM-driven tools to automate data analysis, technical documentation processing, and defect prediction workflows for the 93K IC Test platform
Work under guidance to preprocess datasets, fine-tune open-source LLMs (e.g., LLaMA, Mistral), and integrate retrieval-augmented generation (RAG) systems into testing pipelines
Contribute to MLOps workflows for model training/evaluation using Python frameworks (PyTorch, Hugging Face) and cloud platforms (AWS/Azure)
Participate in 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
Qualifikationen:
University degree in Data Science, Computer Science, Electrical Engineering, or related field (Master's preferred, Bachelor's with 2+ years' experience accepted)
1-3 years of hands-on experience in machine learning, including coursework/practical work with NLP or LLMs
Proficiency in Python for data analysis (Pandas, NumPy) and basic ML model development (scikit-learn, PyTorch)
Familiarity with LLM concepts: transformer architectures, prompt engineering, or text generation techniques
Foundational understanding of MLOps practices - version control (Git/DVC), containerization (Docker), and cloud deployment basics
Basic Linux/Unix command-line skills and ability to work with Jupyter notebooks or VS Code
Strong communication skills in English; ability to document technical work clearly
This is a plus:
Exposure to semiconductor testing data or industrial IoT datasets
Experience with RAG systems or LLM fine-tuning workflows (LoRA, QLoRA)
Basic knowledge of electronic measurement principles (oscilloscopes, parametric analyzers)
Familiarity with Java for integration with existing test platform codebases
Elementary German proficiency
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