Built end-to-end pipelines for document parsing, chunking, vectorisation, and storage in vector databases like FAISS, Pinecone, and Chroma. Job Summary: Develop pipelines to parse documents, chunk, vectorise, and store vector data.
Numbers & Facts
Location
Austin, TX
Salary
$60 Per Hour
Description
Job Summary:
Develop pipelines to parse documents, chunk, vectorise, and store vector data.
Design schemas for vector stores to optimise retrieval efficiency.
Create prompt templates using advanced prompt engineering techniques.
Implement few-shot prompting strategies for improved LLM interactions.
Develop semantic agents and interfaces for seamless agent collaboration.
Build microservices and expose them as APIs for scalable solutions.
Work closely with architects and full-stack developers to deliver AI solutions.
Apply best practices for data management and model deployment.
Ensure scalability and performance of generative AI applications.
Must-Have Skills
Designed and developed scalable generative AI platforms for enterprise use cases.
Built end-to-end pipelines for document parsing, chunking, vectorisation, and storage in vector databases like FAISS, Pinecone, and Chroma.
Created and optimised vector store schemas for efficient semantic retrieval.
Developed prompt templates using few-shot and zero-shot prompting techniques.
Engineered semantic agents and built interfaces for agent collaboration in LLM workflows.
Built and deployed microservices exposing LLM capabilities through scalable APIs.