Generative AI Practice Leader with BFSI Experience

Qualifications

• 12+ years of Proven experience as an Enterprise Architect, Solution Architect, or a similar role, with a focus on AI/Client and generative AI
• Experience in Banking, Insurance and / or Capital Market (BFSI) domain
• Strong understanding of generative AI techniques, including deep generative models, autoregressive models, and reinforcement learning for generative tasks
• At least 5+ years of hands-on experience with building language models, machine learning and AI models leveraging industry tools, products, and / or Azure cognitive services
• Deep and hands-on expertise in (as an individual contributor) Undertaking data collection, Data mining, preprocessing and analysis of structured and unstructured data
• Hands-on expertise in large language models (LLMs/LSTMs/BERT) that can perform complex reasoning in few- and zero-shot settings by generating intermediate chain of thought (CoT) reasoning steps
• Experience of building / customizing and fine-tuning AI models including LLM models via OpenAI (Azure), Bert (AWS) for rapid PoCs
• Experience on LLM Model Governance, LLMSecOps, Hallucination and bias handling
• Strong data science and data engineering background both with open source and cloud distributed machines learning and AI tools especially Azure Cognitive Services, Azure Machine Learning and AWS Sagemaker and Bedrocks

Responsibilities

• Hands-on experience of machine learning methodologies including advanced analytics tools (such as R and Python) along with applied mathematics, Client and Deep Learning frameworks and libraries (TensorFlow, PyTorch, Keras) and Client techniques

Full Description

• 12+ years of Proven experience as an Enterprise Architect, Solution Architect, or a similar role, with a focus on AI/Client and generative AI.

• Experience in Banking, Insurance and / or Capital Market (BFSI) domain

• Strong understanding of generative AI techniques, including deep generative models, autoregressive models, and reinforcement learning for generative tasks.

• Hands-on experience ofmachine learning methodologies including advanced analytics tools (such as R and Python) along with applied mathematics, Client and Deep Learning frameworks and libraries (TensorFlow, PyTorch, Keras) and Client techniques.

• At least 5+ years of hands-on experience with building language models, machine learning and AI models leveraging industry tools, products, and / or Azure cognitive services.

• Deep and hands-on expertise in (as an individual contributor) Undertaking data collection, Data mining, preprocessing and analysis of structured and unstructured data.

• Hands-on expertise in large language models (LLMs/LSTMs/BERT) that can perform complex reasoning in few- and zero-shot settings by generating intermediate chain of thought (CoT) reasoning steps

• Experience of building / customizing and fine-tuning AI models including LLM models via OpenAI (Azure), Bert (AWS) for rapid PoCs

• Experience on LLM Model Governance, LLMSecOps, Hallucination and bias handling

• Strong data science and data engineering background both with open source and cloud distributed machines learning and AI tools especially Azure Cognitive Services, Azure Machine Learning and AWS Sagemaker and Bedrocks