Description

Key Skills: Agentic AI, LLM, AI/ML, Data Scientist, Statistical Analysis, NLP, Retrieval-Augmented Generation (RAG), Semantic AI, Generative AI, Deep Learning

Roles and Responsibilities:

• Design and develop AI agents and multi-agent systems using LangGraph, LangChain, and Semantic Kernel.
• Build and productionize LLM applications using RAG architectures, including retrieval pipelines and ranking strategies.
• Develop machine learning models for classification, regression, forecasting, recommendations, and anomaly detection.
• Implement NLP solutions such as text classification, entity extraction, semantic search, conversational AI, and sentiment analysis.
• Apply statistical modeling and experimental design to validate model performance and drive data-driven decisions.

Skills Required:

• 6-7 years of experience in Data Science and Machine Learning
• Data Science and end-to-end ML solution development
• Statistical Analysis (probability, hypothesis testing, regression analysis, Bayesian statistics, A/B testing)
• NLP and LLM development for semantic understanding and language tasks
• Agentic AI and RAG (retrieval-augmented generation) for enterprise LLM applications

Good to Have:

• Deep Learning and Generative AI experience
• Semantic AI experience

Education: Master's or PhD in Computer Science, Statistics, Mathematics, or a related field (or equivalent practical experience)

Key Skills

Education

Any Graduate