Uday Kiran Chilakala
Ai Machine Learning Engineer @Morgan Stanley
Signup · Get unlimited contacts
WORK HISTORY
Ai Machine Learning Engineer @Morgan Stanley
GA, US
Developed and fine-tuned transformer models (GPT-3, FinBERT, domain-specific LLMs) for financial text classification, sentiment analysis, and fraud detection, achieving an F1-score of 0.92 on unstructured datasets such as earnings reports and market news.• Implemented deep learning–based anomaly detection systems (Autoencoders, GNNs) to identify fraudulent transactions, reducing false positives and investigation time, deployed on AWS SageMaker for real-time scalability.• Built retrieval-augmented AI systems for credit risk assessment and compliance report analysis using RAG and vector databases, improving interpretability and decision-making for risk officers.• Designed end-to-end ML pipelines with CI/CD, monitoring, and experiment tracking (MLflow, W&B), ensuring robustness and auditability for compliance-driven environments.• Automated document processing (KYC, invoices, loan applications) using NLP + CV models, reducing turnaround time for onboarding and regulatory workflows.• Integrated AI-powered chatbots for client service automation and reporting, improving response times while ensuring security and regulatory compliance.• Optimized large-scale data ingestion pipelines with Apache Beam, Spark, and Dataflow, supporting low-latency processing of millions of trades and transactions.• Developed regulatory compliance automation pipelines with RPA tools, streamlining financial statement extraction and regulatory reporting.• Collaborated with quants, risk managers, and compliance teams to deploy ML systems in production, ensuring scalability, security, and adherence to financial regulations.
EDUCATION
Vardhaman College of Engineering (VCEH)
Bachelor of Technology - BTech
Kennesaw State University
Master of Science - MS
ABOUT UDAY KIRAN CHILAKALA
AI/ML Engineer with over 4 years leading the design, development, and deployment of advanced machine learning solutions across finance, banking, and healthcare industries. Skilled in architecting scalable ML infrastructures, integrating deep learning, NLP, and computer vision models, and optimizing end-to-end AI pipelines for both cloud and on-premises environments. Adept at collaborating with cross-functional teams to translate business needs into technical solutions and implementing robust systems for fraud detection, risk management, and automation. Proactive in staying abreast of new AI/ML techniques and technologies, with a strong commitment to delivering security, compliance, and measurable business impact through intelligent systems and modern engineering practices.
This profile is compiled from publicly available professional sources. Unifers is not affiliated with or endorsed by LinkedIn. Request removal of this profile.