RAG Developer

About the Role

Join our team as a Retrieval-Augmented Generation (RAG) Engineering Intern! We're seeking enthusiastic individuals passionate about LLMs, vector databases, and building intelligent information retrieval systems.

What You'll Do

• Implement and optimize RAG pipelines using frameworks like Llama Index, Lang Chain.

• Work with vector databases such as Chroma DB to enhance search capabilities

• Assist in developing, testing, and evaluating RAG components

• Collaborate with the team on improving information retrieval and contextual relevance

Requirements

• Experience with RAG concepts and implementations

• Familiarity with Llama Index or similar frameworks

• Knowledge of vector databases (Chroma, etc.)

• Programming skills in Python

• Strong problem-solving abilities and eagerness to learn

This internship is perfect for those looking to gain hands-on experience in the rapidly evolving field of retrieval-augmented generation while working on real-world applications.