Responsibilities:
- Design, develop and deploy generative models for various applications in Fraud Operations.
- RAG Frameworks - Able to customize and fine-tune existing RAG frameworks or design new RAG to meet project requirements.
- Design and develop POC or full scale solutions on various automations in Operations area including Conversational AI, Multi Agent Systems for multiple services.
- Responsible for development and deployment of Machine Learning or Deep Learning based models.
- Collaborate with cross-functional team to understand business requirements and translate them into AI solutions.
- Conduct research to advance the state-of-the art in generative modeling and stay up to date with latest advancements in the field.
- Optimize and fine-tune models for performance, scalability, and robustness.
- Perform data analysis and preprocessing to ensure high-quality input for model training.
Requirements:
- 8+ years of experience in machine learning and deep learning, with a focus on generative AI solution design and development.
- Strong proficiency in Python and deep learning frameworks such as TensorFlow, PyTorch, or Keras.
- Strong background of Prompt Engineering, building agentic AI or AI Agents, API or MCPs for large scale automations in banking domain.
- Experience with natural language processing (NLP) and natural language generation (NLG).
- Proven track record of building and deploying generative models based solutions in production environments particularly using RAG frameworks.
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