AI/ML

Artificial Intelligence /Machine Learning
WorkMode :Hybrid
Work Location : Chennai / Hyderabad /
Work Timing : 2 PM to 11 PM
Primary : Artificial Intelligence
Job Summary: We are seeking a visionary and technically skilled AI Lead to drive the adoption and development of Artificial Intelligence solutions in the financial services domain. This role will lead the design, development, and implementation of machine learning (ML), deep learning (DL), generative AI and Agent AI solutions that improve decision-making, enhance risk management, and deliver intelligent automation across business functions. The ideal candidate combines deep technical expertise in AI with a strong understanding of financial products, regulatory constraints, and business operations. Lead the development of AI/ML strategies aligned with business goals in areas like credit risk, fraud detection, customer insights, algorithmic trading, and compliance automation. Identify AI opportunities within financial products and services and build a roadmap to deliver value. Develop and deploy predictive models for credit scoring, risk analytics, customer segmentation, and forecasting. Implement NLP-based solutions for document processing, sentiment analysis, chatbots, and regulatory reporting. Use advanced AI techniques including deep learning, reinforcement learning, and LLMs to build next-gen financial intelligence systems. Lead and mentor a team of data scientists and machine learning engineers. Foster collaboration with internal stakeholders including product, compliance, and IT. Drive innovation by staying ahead of industry trends in AI, FinTech, and RegTech. Explore and prototype generative AI/Agent AI use cases for financial advisors, reporting automation, or intelligent document analysis. Bachelors or Masters Degree in Computer Science, Statistics, Machine Learning, or related field. Hands-on experience in building and deploying Generative AI models and Agent AI systems. 7+ years of experience in AI/ML, with at least 2 years in a leadership role. Deep understanding of supervised and unsupervised learning, NLP, time-series modeling, and deep learning. Strong programming skills in Python and experience with ML libraries (TensorFlow, PyTorch, Scikit-learn, XGBoost). Experience working with financial datasets (e.g., transaction data, market data, customer data). Hands-on experience with MLOps and deploying models into production environments (e.g., using AWS, Azure ML, or GCP). Secondary Skills: Experience with financial risk modeling, credit scoring systems, or fraud detection engines. Familiarity with tools like Snowflake, Databricks, SAS, Bloomberg, or FICO. Knowledge of financial regulatory requirements and risk frameworks. Experience integrating AI solutions into financial workflows or trading systems. Published work or patents in financial AI or applied machine learning.