R&D Engineer – AI Integration (m/f/d)
EngineeringOtherAi Integration EngineerR&D Engineer
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Quick Summary
Key Responsibilities
Design, implement, test, and continuously optimize end-to-end RAG (retrieval-augmented generation) pipelines, including data parsing, ingestion, prompt engineering,
Technical Tools
EngineeringOtherAi Integration EngineerR&D Engineer
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.
Responsibilities
~2 min read- →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
Location & Eligibility
Where is the job
De-Munich - Munich, Germany
On-site at the office
Who can apply
DE
About this job
- Who can apply
- Germany
- Posted
- 318 days ago
Listing Details
- Posted
- December 10, 2025
- First seen
- September 25, 2026
- Last seen
- October 24, 2026
Posting Health
- Days active
- 28
- Repost count
- 0
- Trust Level
- 20%
- Scored at
- October 24, 2026
Signal breakdown
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External application
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