Key Responsibilities

• Lead the design, development, and deployment of AIML solutions for the lending and transaction banking businesses, focusing on high-impact areas like credit scoring, risk assessment, payment processing, and fraud detection.
• Architect and implement Deep Learning models using frameworks such as TensorFlow, PyTorch, and other modern ML libraries.
• Drive the development and optimization of NLP models and Large Language Models (LLMs) for applications like automated document processing, customer profiling, and customer interaction.
• Implement vision-based algorithms for document verification, KYC (Know Your Customer) processes, and transaction monitoring.
• Lead a team of engineers and data scientists in developing enterprise-level AIML solutions at a fast pace, ensuring that solutions align with both business and technical requirements.
• Collaborate with business stakeholders to understand the business processes, define AI-driven features, and ensure smooth integration of machine learning models into the existing technology stack.
• Ensure best practices in machine learning lifecycle management, including model training, tuning, and deployment in enterprise environments.
• Guide the team in managing the scalability, performance, and robustness of AI solutions, ensuring they meet the needs of enterprise software systems in transaction banking and lending.

Requirements

• 10+ years of experience in developing and deploying AIML solutions, with at least 2 years of experience in enterprise software development.
• Expertise in Deep Learning frameworks like TensorFlow, PyTorch, and Keras.
• Strong proficiency in Java, Python, and related programming languages.
• In-depth understanding of Natural Language Processing (NLP), with experience working on LLMs (e.g., GPT models, BERT).
• Experience with vision-based algorithms and their application in real-world financial problems.
• Knowledge of business processes in the lending domain and transaction banking.
• Proven track record of building scalable and robust AI solutions in enterprise environments.
• Strong problem-solving skills, with the ability to adapt AIML approaches to rapidly evolving business needs.

Preferred Qualifications

• Previous experience in the lending, transaction banking, or fintech industries.
• Familiarity with enterprise software architecture and integration patterns, especially in the context of financial services.
• Hands-on experience with MLOps practices and tools for deploying and maintaining machine learning models in production.