In this role, you will:

• Design, develop, and fine-tune Generative AI models (e.g., GPT, BERT, Stable Diffusion, etc.) for various use cases such as text generation, summarization, image generation, and more. 

• Build and deploy scalable AI/ML pipelines using Python and frameworks like TensorFlow, PyTorch, or Hugging Face. 

• Integrate Generative AI models into production systems and APIs for real-time or batch processing. 

• Collaborate with cross-functional teams to identify AI use cases and deliver end-to-end solutions. 

• Optimize model performance, reduce latency, and ensure scalability for production environments. 

• Conduct research and stay updated on the latest advancements in Generative AI and machine learning. 

• Work with large datasets, preprocess data, and ensure data quality for training and evaluation. 

• Implement monitoring and logging for deployed AI models to ensure reliability and performance. 

• Write clean, maintainable, and well-documented Python code for AI/ML projects. 

To be successful in this role, you should meet the following requirements:

• Experience with fine-tuning and deploying Large Language Models (LLMs) like OpenAI GPT, Google T5, or similar. 

• Knowledge of Natural Language Processing (NLP) techniques such as tokenization, embeddings, and transformers. 

• Familiarity with MLOps tools and practices for model deployment, monitoring, and lifecycle management. 

• Experience with containerization tools like Docker and orchestration platforms like Kubernetes. 

• Understanding of ethical AI practices and bias mitigation in Generative AI models. 

• Experience in AWS / Cloud Technologies 

• Experience with banking systems