Role & responsibilities Key Responsibilities: Derive and design use cases from structured and unstructured data. Provide LLM expertise to solve AI problems using state-of-the-art language models and off-the-shelf LLM services such as OpenAI models. Apply Retrieval-Augmented Generation (RAG) and relevant techniques to enhance LLM performance and capabilities. Develop end-to-end machine learning pipelines, including model development, tuning, implementation, deployment, and MLOps. Build and fine-tune transformer-based deep learning models. Collaborate with business and product teams to develop and implement analytics-driven AI solutions. Communicate findings and results to both technical and non-technical audiences. Stay updated with the latest research and innovations in AI, ML, Deep Learning, and Generative AI. Mandatory Skills: Python, Scikit-learn, PyTorch, Transformers, SQL, LangChain Model building, hyperparameter tuning, performance evaluation, and deployment Deep Learning / LLM model fine-tuning and evaluation Preferred candidate profile