We are seeking a talented and motivated intern to join our dynamic team at Nokia R&D department, you will have the opportunity to work on cutting-edge RAG (Retrieval-Augmented Generation) tools and contribute to our AI-powered solutions. As an intern, you will gain valuable experience and insights into the world of AI and its applications.
Your responsibilities
- Participate in the development and optimization of RAG-related AI tools, focusing on data retrieval and knowledge enhancement.
- Assist in building and maintaining front-end and back-end functionalities for efficient information retrieval and generation.
- Contribute to data processing, RAG workflow, Agent workflow, admin backend, and API interface development.
- Conduct performance testing, monitoring, and optimization for RAG systems.
- Develop Teams interfaces to enhance collaboration and communication.
- Write clear and concise technical documentation to support the team.
- Collaborate with a diverse team of experts in AI and software development.
- Stay updated with the latest advancements in AI and RAG technologies.
- Provide innovative ideas and solutions to improve our RAG tools.
- Ensure the quality and reliability of our AI-powered systems.
Your skills and experience
- Currently pursuing a bachelor's or master's degree in Computer Science, Artificial Intelligence, or a related field.
- Proficient in Python programming with a solid understanding of data processing and back-end development.
- Experience in front-end development using HTML, JavaScript, and CSS is highly desirable.
- Prior exposure to RAG, NLP, information retrieval, or LLM-related projects is an asset.
- Strong problem-solving skills and a passion for AI and software development.
- Excellent communication and teamwork abilities.
- A keen interest in staying updated with the latest AI trends and technologies.
- Ability to work independently and manage multiple tasks effectively.
- Familiarity with Python web frameworks (Flask, Django) is a plus.
- Experience with mainstream large model API usage and fine-tuning is advantageous.
