Senior AI Scientist

Role Overview: As a member of the AI team at WNS (Holdings) Limited, you will be responsible for building and deploying GenAI models for text generation and content automation. Additionally, you will be involved in fine-tuning and operationalizing Large Language Models (LLMs) for Natural Language Processing (NLP) tasks. Your role will also include developing agentic AI systems with autonomous task planning and decision-making capabilities. Key Responsibilities: - Build and deploy GenAI models for text generation and content automation - Work with latest AI stacks like Nvidia- Nemo, NIM Microservices, Unsloth, Pytorch, Tensorflow, etc. - Develop agentic AI systems with autonomous task planning and decision-making capabilities - Fine-tune and operationalize LLMs (e.g., GPT, Llama, BERT) for NLP tasks using Nemo, NIM, Unsloth frameworks - Establish best practices for LLMOps, including prompt engineering and monitoring - Develop solutions based on latest coding standards like Pep-8 - Experience in developing NLP components like QnA, chatbots, image/video/audio processing, OCR-based components like Extraction, etc. - Design and implement end-to-end pipelines for Retrieval-Augmented Generation (RAG), including document indexing and retrieval mechanisms - Evaluate AI solutions using appropriate metrics Qualifications: - B. Tech. (Note: No additional details about the company were included in the provided job description) Role Overview: As a member of the AI team at WNS (Holdings) Limited, you will be responsible for building and deploying GenAI models for text generation and content automation. Additionally, you will be involved in fine-tuning and operationalizing Large Language Models (LLMs) for Natural Language Processing (NLP) tasks. Your role will also include developing agentic AI systems with autonomous task planning and decision-making capabilities. Key Responsibilities: - Build and deploy GenAI models for text generation and content automation - Work with latest AI stacks like Nvidia- Nemo, NIM Microservices, Unsloth, Pytorch, Tensorflow, etc. - Develop agentic AI systems with autonomous task planning and decision-making capabilities - Fine-tune and operationalize LLMs (e.g., GPT, Llama, BERT) for NLP tasks using Nemo, NIM, Unsloth frameworks - Establish best practices for LLMOps, including prompt engineering and monitoring - Develop solutions based on latest coding standards like Pep-8 - Experience in developing NLP components like QnA, chatbots, image/video/audio processing, OCR-based components like Extraction, etc. - Design and implement end-to-end pipelines for Retrieval-Augmented Generation (RAG), including document indexing and retrieval mechanisms - Evaluate AI solutions using appropriate metrics Qualifications: - B. Tech. (Note: No additional details about the company were included in the provided job description)