RAG Expert Innovacio Technologies

  • company name Innovacio Technologies
  • working location Office Location
  • job type Full Time

Experience: 3 - 3 years required

Pay:

Salary Information not included

Type: Full Time

Location: All India

Skills: RAG RetrievalAugmented Generation expert, RAG models, LLM Monitoring tools, Milvus Vector Database, Azure Cloud

About Innovacio Technologies

Job Description

We are seeking an experienced RAG (Retrieval-Augmented Generation) expert to help optimize and fine-tune the performance of our RAG platform. The successful candidate will play a key role in improving the efficiency and scalability of our platform, ensuring seamless functionality and robust performance. This is a contractual position for a period of 1 month, with the possibility of extension based on performance and project needs. The ideal candidate will have a deep understanding of RAG models, expertise in LLM Monitoring tools, and prior experience working with the Milvus Vector Database. Familiarity with Azure Cloud will be considered a significant advantage. Key Responsibilities: Optimize and fine-tune the performance of the existing RAG platform. Implement DevOps best practices to enhance platform efficiency, scalability, and reliability. Collaborate with the development team to ensure smooth integration and deployment pipelines. Work with Milvus Vector DB for vector database optimization and data handling. Monitor, troubleshoot, and resolve any issues related to platform performance. Ensure secure and scalable infrastructure using cloud technologies. Preferred Qualifications: Proven experience in optimizing RAG platforms. Hands-on experience with Milvus Vector Database. Bonus: Familiarity with Azure Cloud services and infrastructure Add screening questions also Do you have previous working experience on any Vector Database (required) Do you have any working experience with Milvus Vector DB (optional) Do you know how to use LangChain in LLM (required) Do you have any experience with LLM Monitoring tools (optional),