R&D Engineer - AI Integration (m/f/d)

R&D Engineer - AI Integration (m/f/d)

Munich

Advantest Europe GmbH

Kennziffer: 7870

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.

Qualifikation

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 / SmarTest 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, NumPy) 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 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.