Responsibilities : • Develop,Design, develop, and deploy scalable Machine Learning models for predictive analytics, classification, regression, recommendation, clustering, and forecasting problems. • Build end-to-end AI pipelines covering data preprocessing, feature engineering, model training, evaluation, deployment, and monitoring. • Develop and fine-tune Large Language Models (LLMs) for enterprise use cases. • Design and implement Retrieval-Augmented Generation (RAG) architectures using vector databases and embedding models. • Build autonomous AI agents capable of planning, reasoning, memory management, and tool usage. • Contribute to the establishment of best practices for efficient utilization of generative models in business and automation contexts. • Work with leadership and stakeholders to identify AI opportunities and promote strategy. • Be able to deliver solutions following modern software development practices. Required Skills: • • Bachelor's degree in computer science, IT, AI or relevant discipline • Must have minimum of 1 year of work experience in Data Science and Machine Learning, preferably with experience in NLP, Generative AI, LLMs, MLOps/LLMOps, Optimization techniques, and AI solutions. • Specific experience in GenAI and Conversational AI – LLMs, frameworks like Lang chain, Llama Index etc, Vector DBs like Pinecone, Elasticsearch, etc. • Solid proficiency in Python programming and related AI/ML libraries. • Experience with cloud platforms (AWS, Azure, or GCP) for deploying and scaling AI/ML solutions. • Experience with AI model evaluation, prompt optimization, and implementation of Responsible AI practice • Knowledge of API integration, microservices architecture, and production-grade AI application deployment. • Design GenAI application, integrating advanced models like OpenAI’s GPT, BERT or Open Source LLMs. • Deep understanding of the RAG architecture and its implementation. • Knowledge in SQL generation using LLM is preferred. • Ability to write high-quality, maintainable code and work collaboratively. • Knowledge of Agile software development lifecycle, including experience of applying change control procedures and disciplines required. • Problem solving with strong analytical skills with the ability to analyse complex requirements and define technical / functional advanced solutions. • Excellent communication skills in both verbal and written English