Job Description

Roles & Responsibility: Design and optimize language models that can analyze and understand textual data. Your work will enable us to uncover meaningful patterns, trends, and insights from unstructured information, ultimately solving analytical use cases. Utilize sophisticated algorithms and methodologies to refine and improve the performance of our models, enabling accurate predictions and actionable outputs for analytical use cases. Stay informed about the latest advancements in NLP and LLM models and help us identify and adopt cutting-edge techniques. Enable us to continuously improve our language models and effectively address diverse analytical use cases. Work closely with cross-functional teams to address complex business challenges using LLM models. Help define the requirements to build and scale large language models across our customer base. Own and deliver AI enablement projects, including building POCs and delivering thought leadership. Provide data-driven insights and recommendations that support decision-making processes and enable us to overcome analytical hurdles. Document your methodologies, experiments, and results in clear and concise terms. Effectively communicate complex concepts and findings to both technical and non-technical stakeholders. Educating individuals or teams on the concepts, tools, and applications of Generative AI technologies, blending training, technical expertise, and practical guidance. Qualifications: A minimum of 5 years of experience in analytics preferably in Banking and Financial Services A minimum of 3 years of hands-on experience working on NLP, Deep learning and machine learning models and LLMs to solve analytical use cases. Experience working with Large Language Models (LLMs), including various prompt engineering techniques, word embeddings and vector databases. Azure stack (AI Search, OpenAI) and understanding of Agentic Architecture is a plus. Experience with one or more of the following tools and frameworks – LangChain, LangGraph, OpenAI Assistants API, AutoGen, etc. Knowledge of various cloud services (AWS, Azure, GCP) and their management. Experience with cloud native applications and/or deployment is a plus. Excellent problem-solving and analytical skills, with the ability to work on complex projects and deliver high-quality results. Strong knowledge and understanding of Natural Language Processing (NLP) techniques and algorithms, and their practical applications in addressing analytical challenges. Proficiency in Python and having working knowledge of other programming languages is a plus, and experience with NLP libraries. Knowledge of frontend components and full-stack integration is a plus. Experience with large-scale data processing and distributed computing frameworks is a plus. Strong communication skills, both written and verbal, with the ability to convey complex ideas to diverse stakeholders. A track record of staying up to date with the latest advancements in NLP research and incorporating new techniques into practical applications. Show more Show less