R&D Engineer - AI Integration (m/f/d) 15.10.2026 Advantest Europe GmbH Munich

Labo; München; Hybrid; EUR 70,000 - 110,000; Full time

Benefits offered by this job

Flexible working hours

Mobile working

30 vacation days

Bike leasing

Job summary

Advantest seeks an R&D Engineer to develop AI/LLMs-driven solutions for semiconductor test systems. You will build end-to-end AI pipelines, integrate with existing platforms using Java and C++, and fine-tune open-source LLMs.

Collaboration with agile teams and data-driven evaluation are key expectations. Requirements include a Master’s preferred or Bachelor’s with 5+ years of experience, proficiency in Python and ML tools, and knowledge of MLOps, Docker, and cloud deployment.

Qualifications

• University degree in Data Science, Computer Science, Electrical Engineering, or a related field (Master's preferred, Bachelor's with 5+ years' experience accepted)
• 2-4 years of hands-on experience in machine learning, including NLP/LLMs
• Proficiency in Python for data analysis and ML model development
• Experience with Java and C++
• Familiarity with Linux and command-line tooling
• Knowledge of MLOps concepts (Git/DVC, Docker, cloud deployment) and Jupyter/VS Code

Responsibilities

• Design, implement, test, and optimize end-to-end RAG pipelines including data parsing, ingestion, prompt engineering and chunking strategies
• Integrate AI components with existing systems using Java and C++
• Curate and develop high-quality datasets including synthetic data for robust training and evaluation of LLMs
• Fine-tune open-source LLMs (e.g., LLaMA, Mistral) and integrate RAG systems into testing pipelines
• Evaluate LLM applications for correctness, latency and hallucinations
• Assist in deploying LLM-based applications and analyze user feedback for iterative improvements
• Write clean, maintainable code and follow software engineering best practices
• Collaborate with cross-functional agile teams to translate customer requirements into prototypes
• Analyze semiconductor testing data using statistical methods and visualization tools
• Contribute to MLOps workflows for model training, evaluation and deployment (Python, PyTorch, Hugging Face)
• Work in Linux environments, use command-line tools, scripting and system operations

Skills

Python

PyTorch

Hugging Face

Java

C++

Linux

Eclipse

DL/ML

MLOps

Git/DVC

Docker

Cloud (AWS/Azure)

Jupyter/VS Code

LLMs

Education

University degree in Data Science

Master's preferred

5+ years experience (Bachelor's acceptable)

Tools

Jupyter

VS Code

Docker

Git

Job description

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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.

• 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
• 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
• Flexibility
• Development
• Fitness
• Security
• Flexible and trust-based working hours, 30 vacation days + option for additional vacation days, mobile working, individual part-time models and programs for extended periods of absence
• Attractive salary, share in Advantest´s success through our exceptionally appealing bonus program as well as numerous subsidies, discounts and offerings (e.g. bike leasing)
• Structured onboarding programs and mentoring, development discussions, technical and soft skill trainings, language courses and knowledge sessions
• Ergonomic working environment, sports and fitness options and events (e.g. Global Challenge) as well as health days
• Attractive company pension scheme, comprehensive insurance coverage and support in emergency situations