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Open nowPosted 319 days ago

R&D Engineer – AI Integration (m/f/d)

Advantest288 open roles

Where
Munich, DEU
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Your applicationOpen nowR&D Engineer – AI Integration (m/f/d)Advantest · Munich, DEU

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The clock on this job

Early applications get read.

12.1% of postings close within 7 days. Measured by our own scanner across the market. Advantest postings stay open a median of 1 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.1%7 days
  4. 19.1%14 days
  5. 35.6%30 days
  6. 52.7%60 days
This job: posted 319 days ago

Advantest median: 1 days open

The posting

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
  • 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
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