About the Role: We are seeking a highly motivated intern with strong coding skills and a solid foundation in machine learning and data science, to help us develop and prototype Generative AI applications. You will work closely with our engineering and research teams to build intelligent systems that combine LLMs with external tools, APIs, and knowledge bases. Key Responsibilities: • Design, prototype, and evaluate GenAI applications such as: - Retrieval-Augmented Generation (RAG) pipelines - Autonomous or semi-autonomous AI agents - LLM-based tools for reasoning, summarization, and decision-making • Integrate LLMs with vector databases, APIs, and external data sources. • Implement prompt engineering and fine-tuning strategies for LLMs. • Write clean, efficient, and well-documented code (primarily in Python). • Conduct experiments to evaluate performance, reliability, and scalability. • Collaborate with team members to iterate on ideas and deliver working prototypes. Qualifications: • Currently pursuing a Master's or PhD in Computer Science, Engineering, or a related field. • Strong programming skills in Python and experience with modern ML frameworks. • Familiarity with LLMs and AI development frameworks (e.g., OpenAI, Hugging Face Transformers, LangGraph, LlamaIndex, etc.). • Understanding of NLP/LLM related concepts, vector search, and embedding models. • Experience with vector databases like FAISS, Weaviate, Pinecone, or similar. • Solid grasp of software engineering practices (e.g., Git, CI/CD, Containers). Preferred Qualifications: • Experience building RAG systems or AI agents. • Familiarity with cloud platforms (AWS, GCP, Azure). • Knowledge of MLOps or LLMOps workflows. • Contributions to open-source GenAI projects or research.