Applied Scientist - LLM / VectorDB

Description :

We are seeking a high-calibre Applied Scientist to drive innovation in our core information retrieval capabilities.

This critical role demands deep expertise in building high-performance Machine Learning systems that enhance search relevance, retrieval efficiency, and user experience.

You will be responsible for pioneering the implementation of Vector Search, Hybrid Search, and LLM-powered RAG systems at scale.

Key Responsibilities & Strategic Deliverables :

1. Search & Ranking System Development :

• ML Pipeline Ownership : Design, build, and deploy robust, production-ready ML pipelines specifically for large-scale search and ranking applications.
• Advanced Retrieval : Lead the implementation and optimization of vector search, hybrid search, and advanced Learning-to-Rank (LTR) systems to maximize relevance and precision.
• Embedding Management : Drive the entire embedding lifecycle, including embedding generation using state-of-the-art models (e.g., BERT, Sentence Transformers) and managing high-scale embedding indexes using efficient libraries like FAISS, ScaNN, or Annoy.

Generative AI & Cloud Deployment :

Evaluation, Testing & Optimization :

Required Skills & Technical Expertise :

Core Fundamentals (Mandatory) :

(ref : hirist.tech)