Description

You design, develop, and optimize AI/ML models and LLM-based solutions, focusing on RAG systems and knowledge graphs to enhance AI reasoning and retrieval.

This role is on-site.

Responsibilities

• Build and improve Retrieval-Augmented Generation (RAG) systems for AI applications.
• Develop knowledge graph and Neo4j-based solutions to improve model reasoning.
• Design, develop, and optimize AI/ML models using Python and deep learning frameworks.
• Deploy and manage ML solutions using cloud platforms and MLOps practices.
• Conduct experiments, analyze results, and iterate to improve model performance.

Required Skills

• 5-9 years of experience in AI/ML development and LLM-based systems.
• Strong proficiency in Python and machine learning concepts.
• Hands-on experience with Large Language Models (LLMs) and RAG architectures.
• Experience with knowledge graphs, graph databases (Neo4j), and data preprocessing.
• Understanding of PyTorch, TensorFlow, and MLOps principles.
• Familiarity with cloud ML platforms, specifically AWS and Azure.

Preferred Skills

• Experience with Databricks or GPU-based ML solutions.

Key Skills

Education

Any Graduate