Job
Description
Company Description WNS (Holdings) Limited (NYSE: WNS), is a leading Business Process Management (BPM) company. We combine our deep industry knowledge with technology and analytics expertise to co-create innovative, digital-led transformational solutions with clients across 10 industries. We enable businesses in Travel, Insurance, Banking and Financial Services, Manufacturing, Retail and Consumer Packaged Goods, Shipping and Logistics, Healthcare, and Utilities to re-imagine their digital future and transform their outcomes with operational excellence.We deliver an entire spectrum of BPM services in finance and accounting, procurement, customer interaction services and human resources leveraging collaborative models that are tailored to address the unique business challenges of each client. We co-create and execute the future vision of 400+ clients with the help of our 44,000+ employees. Job Description Generative & Agentic AI Build and deploy GenAI models for text generation and content automation. Experience on working latest AI stacks like Nvidia- Nemo, NIM Microservices, Unsloth, Pytorch, Tensorflow etc. Develop agentic AI systems with autonomous task planning and decision-making capabilities.2. Large Language Models (LLMs) Fine-tune and operationalize LLMs (e.g., GPT, Llama, BERT) for NLP tasks using Nemo, NIM, Unsloth etc frameworks Establish the best practices for LLMOps, including prompt engineering and monitoring. Develop solution based on latest coding standards like Pep-83. Deep Learning and NLP components Experience in developing like QnA, chatbots, Image/Video/Audio processing, OCR based components like Extraction etc. Experience in designing and implementing end-to-end pipelines for Retrieval-Augmented Generation (RAG), including document indexing, retrieval mechanisms Experience in evaluating AI solutions using appropriate metrics Qualifications Bachelors or master’s in computer science, Artificial Intelligence, or a related field2. 7+ years of experience in AI/ML, NLP, Deep Learning, Gen AI, Model fine tuning, Reinforcement learning, etc. Show more Show less
