Data Scientist

Design, build, and optimize advanced Retrieval Augmented Generation (RAG) architectures to improve enterprise search and knowledge systems.
Develop and deploy scalable language models and Natural Language Processing (NLP) solutions using frameworks like LangChain.
Implement highly efficient vector search databases leveraging vector indexing libraries such as FAISS.
Benchmark, evaluate, and fine-tune Large Language Models (LLMs) systematically using modern LLM evaluation metrics.
Write robust, well-structured production-grade code leveraging python environments and data pipelines.
Collaborate closely with cloud and engineering teams to integrate intelligent AI solutions into core products.
Cleanse, engineer, and prepare structured and unstructured data assets to ensure high data readiness for model training.

Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or a related quantitative technical stream.
4–9 years of professional software engineering or core data science development experience.
Strong, verifiable hands-on expertise working extensively with Python, NLP pipelines, and LLM architectures.
Thorough conceptual and practical clarity in deploying vector search indexes and advanced RAG workflows.
Exceptional technical documentation, system troubleshooting, and analytical problem-solving capabilities.