US Data Scientist - Artificial Intelligence

* Generative AI and Large Language Models (LLMs) * Agentic AI and Multi-Agent Systems * RAG Architecture and Semantic Search * Prompt Engineering * Fine-Tuning and Model Evaluation * Custom ML Model Development * Classification Models * Clustering Models * Recommendation Systems * Predictive Analytics * Feature Engineering * MLOps and Model Lifecycle Management ### Frameworks & Libraries * LangGraph * AutoGen * LangChain * CrewAI (preferred) * MCP (Model Context Protocol) * OpenAI APIs * Anthropic Claude APIs * Hugging Face Ecosystem * Scikit-Learn * XGBoost * PyTorch * TensorFlow (preferred) ### Data & Analytics Platforms * Snowflake * Databricks * SQL * Vector Databases * Feature Stores * Data Warehousing Concepts ### Backend & APIs * Python * Flask * REST APIs * FastAPI

 

### Cloud & DevOps * Client Azure * Azure Kubernetes Service (AKS) * Docker * Kubernetes * CI/CD Pipelines * Azure DevOps * GitHub ### Front-End (Good to Have) * React * Angular --- ## Preferred Experience * Building enterprise AI assistants and conversational platforms. * Developing AI-powered analytics and decision-support systems. * Designing agent orchestration frameworks and workflow automation platforms. * Working with telecom, marketing analytics, customer intelligence, or large-scale enterprise datasets. * Experience handling datasets with millions of records and deploying AI solutions at scale. * Exposure to AI governance, responsible AI, and model monitoring frameworks