Sai Mahesh B

About Sai Mahesh B

I am an AI/ML Engineer with 4+ years of experience transforming data into real-world impact across finance, healthcare, and enterprise applications. My expertise spans Generative AI, NLP, Computer Vision, and Predictive Analytics, and my passion lies in building intelligent systems that are not only accurate but also scalable, explainable, and compliant with industry regulations. At Genworth Finance, I built and deployed deep learning models (CNNs, LSTMs, GPT-4, LLaMA) that boosted anomaly detection accuracy by 30%, saved analysts 10+ hours per week, and prevented $500K in annual fraud losses. I also designed Retrieval-Augmented Generation (RAG) pipelines with LangChain and LlamaIndex, reducing compliance document search time by 40%, and deployed scalable ML workflows on AWS, GCP, and Azure. Previously at Citius Tech, I engineered predictive models that improved patient risk forecasting by 15% and optimized operational efficiency by 20% through advanced dashboards in Power BI. I also accelerated clinical text analytics using NLP techniques, improving summarization and extraction workflows across healthcare datasets.

Experience

1. Machine Learning Engineer

   Genworth

   Aug 2024 — Present · US

   Developed deep learning models (CNNs, LSTMs, BERT, GPT-4) for fraud detection and credit risk, improvinghigher anomaly detection by 30%, saving 10 hours/week per analyst, and preventing $500K in annual losses Fine-tuned pre-trained ML and deep learning models (BERT, LLaMA, XGBoost) on insurance and financialdatasets and deployed them using AWS SageMaker, reducing model retraining time by 55% and enablingreal-time predictions for fraud and risk analysis Designed and executed A/B testing and hypothesis testing on fraud detection and risk assessment models,improving transaction monitoring accuracy by 27% and reducing false positives Implemented Retrieval-Augmented Generation pipelines with LangChain and LlamaIndex, enabling financialadvisors to query large volumes of policy and compliance documents, reducing manual lookup time by 40% Leveraged Azure Data Factory & Synapse to build end-to-end ETL pipelines integrating structured andunstructured financial data, improving data accessibility and accelerating analytics for fraud and policymanagement Collaborated with cross-functional teams to deploy scalable ML pipelines on AWS, GCP, and Azure, presentinginsights to non-technical stakeholders and reducing model training time by 60%, enabling data-driven decisionsacross healthcare and finance Implemented robust data governance frameworks and ensured GDPR compliance across sensitive financialdatasets, safeguarding customer data, and maintaining regulatory adherence.

Education

• REVA University

  Bachelor's degree

  2016 — 2019

• Colorado State University

  Master's degree

  2024 — 2025