R&D Engineer - AI Integration; m​/f​/d

Stellenbezeichnung: Wir suchen: R&D Engineer - AI Integration (m/f/d)
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R&D Engineer - AI Integration (m/f/d)
Advantest Europe GmbH Munich Vollzeit Home-Office
Advantest - We enable tomorrowʻs technology.
Market leader Hightech-High-tech semiconductors International impact
IoT, 5G and Artificial Intelligence. Unthinkable without us. More than half of all the microchips produced worldwide first pass through our hands. As the global market leader of automated test systems in the semiconductor industry we help the world to realize the digital transformation, enable our customers to shape the future and offer you the exciting jobs intended for pioneers.

You work in international teams with a high degree of personal responsibility and short communication channels.
Your Responsibilities

Role Overview :
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 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, C++ and familiarity with Eclipse Work in Linux environments and handle command-line tools, scripting, and system operations
Your Qualifications
University degree in Data Science, Computer Science, Electrical Engineering, or a related field (Master's preferred, Bachelor's with 5+ years' experience accepted)

Experience with Advantest V93000 test systems / Smar Test 8 Experience in Eclipse Plugin development 2-4 years of hands-on experience in machine learning, including coursework or practical work with NLP or LLMs Proficiency in Python for data analysis (Pandas, Num Py) and ML model development (scikit-learn, PyTorch) Experience programming in Java and 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…