Intern-AI Application SW & Data

The primary goal of this position is to design, implement, and maintain cost-efficient, high-quality test software for Radio products, deployed on Industrial PC and Cloud-based platforms. Responsibilities (Application Software Development AI & Data Direction) The main responsibilities of this position include: • Design and develop AI-powered application prototypes using modern Generative AI technologies. • Implement Retrieval-Augmented Generation (RAG) pipelines for knowledge retrieval and question-answering systems. • Develop and experiment with AI agents and multi-step reasoning workflows for automation and decision support. • Build backend components and APIs for AI applications using Python. • Integrate LLM services from platforms such as OpenAI API or Azure OpenAI Service. • Work with AI frameworks such as LangChain or LlamaIndex to develop intelligent workflows. • Implement document processing pipelines including chunking, embedding generation, and vector retrieval. • Evaluate and improve LLM performance through prompt engineering, evaluation datasets, and experimentation. Qualifications • Education Background: Bachelor’s or master’s degree in data science, Computer Science, Artificial Intelligence, or related fields. • Strong programming skills in Python. • Basic understanding of Large Language Models (LLMs) and Generative AI. • Familiarity with natural language processing concepts, such as embeddings, semantic search, and vector similarity. • Experience with Git-based collaborative development workflows. • Strong analytical and problem-solving skills. • Ability to quickly learn new technologies and work in a fast-evolving AI landscape. • Good communication skills and ability to work in a team environment. • Fluent in English for speaking and writing. Nice-to-have • Experience building RAG-based systems using vector databases (e.g., FAISS or Pinecone). • Experience developing AI agents or LLM workflows. • Familiarity with prompt engineering and LLM evaluation techniques. • Experience with cloud platforms such as Microsoft Azure or Amazon Web Services. • Experience working on AI-related research projects or publications.