About the Position:
* We are seeking an experienced AI/ML engineer to develop and optimize Retrieval-Augmented Generation (RAG) models for search across large-scale medical and scientific documents.
* The primary focus will be on building and embedding RAG models for efficient search, including pre-processing and contextual accuracy.
Key Responsibilities:
* Develop and optimize RAG models for search
* Implement semantic chunking strategies
* Enhance the automated evaluation pipeline
* Fine-tune Large Language Models (LLMs) for textual RAG use cases
Requirements:
* At least 1 year of experience as a Search Engineer or AI/ML Engineer
* Search Technology Experience – OpenSearch, building scalable search systems
* 2+ years of Python development experience, including API creation, model training, testing, and general backend programming
* Familiarity with LangChain for building LLM workflows using tools, memory, and retrieval.
Nice to Have Skills:
* Familiarity with AWS infrastructure (IAM, VPC, S3, etc.)
* Exposure to RAG architectures, specifically textual RAG use cases
About the Opportunity:
This is an excellent chance to work on challenging projects, collaborate with experts, and grow your skills in AI/ML engineering.