Experience : 4Yrs - 10 Yrs

Build GenAI applications using Python for tasks like summarization, chatbots and intelligent automation.
Fine tune and deploy LLMs and traditional ML models for classification, prediction, and decisioning.
Design solutions using embeddings, vector search, and retrieval augmented generation (RAG).
Integrate models with AWS services like SageMaker, Lambda, Bedrock and data platforms like Snowflake.
Collaborate across teams to embed AI/ML into business workflows and automation pipelines.

Preferred Skills

Strong Python skills with experience in GenAI frameworks like LangChain, Hugging Face, OpenAI.
Solid grounding in ML algorithms, model training and evaluation.
Familiarity with prompt engineering, tokenization and model optimization.
Hands-on with AWS tools for scalable deployment and serverless execution.
Ability to connect models to APIs, data sources and orchestration tools.
Build GenAI applications using Python for tasks like chatbots, summarization and intelligent automation.
Develop and fine tune LLMs and ML models for classification, prediction, and decision support.
Design solutions using embeddings, vector search, and retrieval augmented generation (RAG).
Deploy models using Azure Machine Learning and Azure OpenAI scale with Azure Functions and Cognitive Services.
Integrate AI systems with APIs, enterprise data platforms and business workflows.

Preferred Skills

Strong Python development with experience in GenAI frameworks like LangChain, Hugging Face, OpenAI.
Solid foundation in ML algorithms, training pipelines and evaluation techniques.
Familiarity with prompt engineering, tokenization and model optimization.
Hands-on with Azure cloud tools for model lifecycle, deployment,and serverless execution.
Ability to connect models to data sources, automation tools and orchestration platforms.

Lead-Data Insight & Automation