Description

Skills:
Strong Python programming skills:
Demonstrated proficiency in Python programming, including experience with relevant libraries and frameworks
Experience with LLMs and RAG systems:
Familiarity with large language models and retrieval-augmented generation techniques, including experience with LLM APIs and retrieval systems.
Experience with data retrieval and indexing:
Experience with data retrieval from various sources (e.g., databases APIs, file systems) and building and managing retrieval indices.
Knowledge of data structures and algorithms:
Understanding of fundamental data structures and algorithms relevant to building efficient and scalable RAG applications.
Experience with cloud computing platforms (e.g., AWS, GCP, Azure):
Familiarity with cloud computing platforms and their services for deploying and scaling RAG applications.
Strong problem-solving and analytical skills:
Ability to identify, analyze, and solve complex problems related to data retrieval, LLM integration, and RAG system optimization.
Bonus Points:
Experience with specific LLM frameworks (e.g., LangChain, Hugging Face Transformers).
Familiarity with search engines and information retrieval techniques.
Experience with machine learning and deep learning concepts.
Experience with building and deploying production-ready applications.
Contribution to open-source projects related to RAG or LLMs.
 

Key Skills
Education

Any Graduate