Intern(Temporary Associate) – Technical Assessment and Monitoring (Risk Advisory)
Job Description Summary
*Purpose of the role in 1-2* *sentences*
This role requires the candidate to be involved in building and deploying AI/ML solutions, working across Python, Large Language Models, RAG pipelines, and Full Stack Development, while collaborating with the engineering team to deliver intelligent, production-ready applications.
Job Description
*3-5 bullet points of* *specific duties*
About the Role:
- Solid understanding of Machine Learning concepts — supervised, unsupervised learning, model training and evaluation.
- Knowledge of Large Language Models (LLMs) such as OpenAI GPT, Claude, Gemini, LLaMA, or Mistral
- Understanding of Prompt Engineering and LLM API integration
- Knowledge of RAG (Retrieval-Augmented Generation) architecture and its real-world applications
- Exposure to LLM orchestration tools — LangChain or LlamaIndex
- Basic familiarity with Vector Databases — Pinecone, FAISS, or ChromaDB
- Basic knowledge of backend frameworks — FastAPI or Flask for REST API development
- Understanding of Full Stack Development — React or Next.js (Frontend), Python-based Backend
- Familiarity with databases — Firebase, PostgreSQL, MongoDB
*3-5 bullet points of key* *selection criteria*
About You:
Bachelor’s in computer science / information technology / Artificial Intelligence & Machine Learning Currently pursuing T.E. (Third Year) or Final Year of graduation
- Basic to intermediate hands-on knowledge of Python and its core libraries
- Familiarity with Machine Learning concepts and model building
- Exposure to Large Language Models and Generative AI tools
- Ability to understand and work with RAG pipelines and vector databases
- Academic or personal projects related to AI / ML / LLM / Full Stack Develo