Data Scientist

Minimum of 5+ years of professional experience in Python programming and data-related fields. Minimum of 2 years of hands-on experience in designing and implementing RAG (Retrieval-Augmented Generation) systems. Demonstrable experience with Agentic AI frameworks (e.g., Semantic Kernel, LangChain, LangGraph, etc.). Experience with Semantic Kernel is highly desirable. Very solid, hands-on experience with core AWS services relevant to AI/ML and software development (e.g., S3, EC2, Lambda, SageMaker, DynamoDB, etc.). Expertise in modern software development practices, including Git/GitHub, Agile methodologies (Scrum/Kanban), and CI/CD pipelines. Exposure to .net stack Strong experience with Data Deep understanding of large language models (LLMs) and their application in real-world scenarios. Excellent problem-solving skills and the ability to work independently and as part of a team. Strong communication and collaboration skills. Experience with MLOps and productionizing machine learning models Familiarity with containerization technologies like Docker and orchestration tools like Kubernetes.
focus on Agentic use cases. Experience with using open source LLMs, Langchain, Langgraph with real life use cases. Would also prefer a background in building and operationalizing Machine Learning Models where they have done feature engineering, model training etc focus on Agentic use cases. Experience with using open source LLMs, Langchain, Langgraph with real life use cases. Would also prefer a background in building and operationalizing Machine Learning Models where they have done feature engineering, model training etc focus on Agentic use cases. Experience with using open source LLMs, Langchain, Langgraph with real life use cases. Would also prefer a background in building and operationalizing Machine Learning Models where they have done feature engineering, model training etc