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

Advantest Europe GmbH
München, Germany
9 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Shift work
Languages
English, German
Experience level
Junior

Job location

München, Germany

Tech stack

Java
Artificial Intelligence
Amazon Web Services (AWS)
Data analysis
Automation of Tests
Azure
C++
Command-Line Interface
Cloud Computing
Computer Programming
Data Visualization
Linux
Eclipse
Python
Machine Learning
NumPy
Open Source Technology
Software Engineering
Systems Integration
Jupyter Notebook
Scripting (Bash/Python/Go/Ruby)
PyTorch
5G NR
Large Language Models
Prompt Engineering
GIT
Pandas
Containerization
Scikit Learn
Information Technology
HuggingFace
Machine Learning Operations
Software Version Control
Docker
Data Generation

Job description

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.

Are you seeking answers and opportunities for your future? At our site in Munich you will find both as, 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., * Design, implement, test, and continuously optimize end-to-end RAG (retrieval-augmented generation) pipelines, including data parsing, ingestion, prompt engineering, and chunking strategies.

  • 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 or C++ and familiarity with Eclipse.
  • Work in Linux environments and handle command-line tools, scripting, and system operations.

Requirements

  • University degree in Data Science, Computer Science, Electrical Engineering, or a related field (Master's preferred, Bachelor's with 2+ years' experience accepted).
  • 1-3 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 or 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 or 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.

This is a plus:

  • Experience with Advantest V93000 test systems
  • Experience in Eclipse Plugin development

Benefits & conditions

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

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