Lead the design, development, and deployment of AI/ML 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 AI/ML 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
Required Skills
10+ years of experience in developing and deploying AI/ML 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 AI/ML 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.
Benefits
Why Join Us
Work at the cutting edge of AI/ML, focusing on lending and transaction banking use cases.
Lead and mentor a talented team of engineers and data scientists.
Join a fast-paced, dynamic environment where you can drive innovation and deliver impactful AI solutions.
Competitive salary and benefits, along with ample opportunities for professional growth.
