Sairam M

Collaborated with cross-functional teams to collect, pre-process, and analyse large volumes of data from microservices, ensuring data quality and relevance. Established performance baselines for real-time monitoring of 60 microservices. Employed CNNs and Generative AI with Large Language Models for analysis and content generation, enhancing user engagement and personalized interactions. Led AIOPS initiatives to improve system reliability by predicting anomalies. Developed fraud detection algorithms reducing online fraud. Enhanced investment risk management with real-time dashboards. Transformed financial modeling with CNNs and LLMs for improved asset valuation. Created CI/CD pipelines with Azure DevOps, GitHub Actions, Docker, and Kubernetes to automate deployment. Developed multi-channel optimization strategies that improved digital engagement by 10%. Delivered NLP and Computer Vision applications with frameworks like Spacy, TensorFlow, YOLO, and Faster R-CNN. Led R&D efforts on causa

Collaborated with cross-functional teams to analyze large volumes of microservices data, establishing performance baselines and enabling real-time anomaly detection. Led AIOPS initiatives improving system reliability over 60 microservices, developed CNN and Generative AI models for fraud detection and investment risk management, and transformed financial modeling using CNNs and LLMs. Deployed web services on Azure, created CI/CD pipelines with Azure DevOps, GitHub Actions, Heroku, Docker, and Kubernetes. Developed NLP and computer vision applications, productionized causal models optimizing customer retention, and built financial forecasting and demand prediction models boosting business efficiency.

Led data manipulation, visualization, and pipeline efficiency improvements using Tableau and Power BI. Developed a Contextual Intelligence Engine on AWS EMR, achieving a 40% increase in user engagement. Transformed team's workflow by implementing code/model version control and continuous integration with automated testing. Created training programs for modern AI tools and cloud platforms including AWS SageMaker, TensorFlow, and Hugging Face. Championed integration of big data technologies like Spark and Delta Lake. Collaborated on analytics and customer segmentation projects using Snowflake and Tableau. Implemented and maintained over 15 machine learning models from development through deployment. Built Ethical AI frameworks ensuring fairness, explainability, and bias mitigation. Helped develop a no-code ML platform for Customer Success teams. Conducted AI/ML research and experimentation to evaluate new algorithms.