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Metro ML/AI internship with broad LLM/full-stack expectations attracts many student applicants.
ML/LLM and full-stack skills are broadly transferable, though RAG/real-estate specifics slightly narrow applicability.
Requires current student status plus specific ML/LLM and full-stack skills, but no strict years-of-experience.
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Build and deploy AI/ML solutions involving Python, Large Language Models (LLMs), and RAG pipelines.
Collaborate with engineering teams to deliver production-ready intelligent applications.
Incorporate full stack development skills, including backend APIs (FastAPI/Flask) and frontend (React/Next.js).
Currently pursuing Bachelor’s degree in Computer Science, IT, AI, or related field; Third Year or Final Year students eligible.
Basic to intermediate hands-on experience with Python programming and core libraries.
Familiarity with Machine Learning concepts and exposure to LLMs, Prompt Engineering, RAG architecture, and vector databases.
Work Experience Required: Not explicitly mentioned in the JD.
Has academic or personal projects demonstrating AI/ML/LLM and full stack development capabilities.
Capable of understanding and applying RAG pipelines and LLM orchestration tools like LangChain or LlamaIndex.
Comfortable working in a collaborative engineering environment focusing on AI-driven production applications.