Hi, I'm Varsha Ravula, an AI/ML Engineer with 4+ years of experience designing, building, and deploying scalable ML solutions across finance, payments, and healthcare. I specialize in end-to-end ML lifecycle management—from data ingestion and feature engineering to model training, evaluation, deployment, and real-time monitoring—using Python, Apache Airflow, and MLflow. My work combines advanced algorithms, cloud-native infrastructure, and governance to deliver reliable, interpretable AI in production. Outside of development, I focus on collaboration, explainability (SHAP/LIME), and building platforms that remain secure, compliant, and observable. I thrive in Agile teams, embrace IaC for reproducible environments, and design containerized microservices for low-latency inference and scalable experimentation.

Varsha Ravula

Hi, I'm Varsha Ravula, an AI/ML Engineer with 4+ years of experience designing, building, and deploying scalable ML solutions across finance, payments, and healthcare. I specialize in end-to-end ML lifecycle management—from data ingestion and feature engineering to model training, evaluation, deployment, and real-time monitoring—using Python, Apache Airflow, and MLflow. My work combines advanced algorithms, cloud-native infrastructure, and governance to deliver reliable, interpretable AI in production. Outside of development, I focus on collaboration, explainability (SHAP/LIME), and building platforms that remain secure, compliant, and observable. I thrive in Agile teams, embrace IaC for reproducible environments, and design containerized microservices for low-latency inference and scalable experimentation.

Available to hire

Hi, I’m Varsha Ravula, an AI/ML Engineer with 4+ years of experience designing, building, and deploying scalable ML solutions across finance, payments, and healthcare. I specialize in end-to-end ML lifecycle management—from data ingestion and feature engineering to model training, evaluation, deployment, and real-time monitoring—using Python, Apache Airflow, and MLflow. My work combines advanced algorithms, cloud-native infrastructure, and governance to deliver reliable, interpretable AI in production.

Outside of development, I focus on collaboration, explainability (SHAP/LIME), and building platforms that remain secure, compliant, and observable. I thrive in Agile teams, embrace IaC for reproducible environments, and design containerized microservices for low-latency inference and scalable experimentation.

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Experience Level

Expert
Expert
Expert
Expert
Expert
Expert

Language

English
Advanced

Work Experience

AI-ML Engineer at Citi Bank
December 1, 2024 - Present
Spearheaded the development and deployment of a robust AI/ML platform to support fraud detection, credit risk scoring, and real-time decisioning on high-volume financial transaction data. Architected scalable ML pipelines with Apache Airflow and MLflow, enabling end-to-end experiment tracking and reproducibility. Developed fraud detection and credit risk models using PyTorch, TensorFlow, and XGBoost, improving anomaly detection accuracy and reducing false positives in production. Built containerized inference APIs with FastAPI and Docker, deployed on Amazon EKS with Helm, enabling low-latency fraud scoring for mission-critical banking operations. Automated infrastructure provisioning with Terraform for reproducible, multi-account deployments. Integrated TensorFlow Serving, TorchServe, and Triton Inference Server for production inference, and implemented serverless retraining with AWS Lambda and Step Functions. Enforced PCI-DSS/GDPR-aligned data protection, S3/IAM/Secrets Manager govern
ML Platform Engineer at VISA
November 1, 2024 - September 9, 2025
Designed and implemented a scalable ML platform for fraud detection, transaction risk analytics, and secure payment authentication within global payment systems. Automated end-to-end ML pipelines with MLflow, DVC, SageMaker, and Kubernetes to ensure reproducibility, scalability, and CI/CD integration. Delivered low-latency inference REST APIs integrated into payment workflows, enabling millisecond-level checks and regulatory compliance (PCI-DSS, GDPR). Built monitoring and alerting for model drift and infra health. Managed cloud-native training and batch inference workloads on AWS SageMaker, optimizing cost with managed compute resources and spot instances. Implemented RBAC and secrets management; deployed containerized microservices on Kubernetes with Helm; automated CI/CD with GitHub Actions and Jenkins. Collaborated with data scientists and engineers in Agile teams to deliver compliant, production-grade ML components.
Junior Machine Learning Engineer at SigTuple (Premier Inc)
December 1, 2022 - September 9, 2025
Contributed to the AI/ML platform for diagnostic imaging and healthcare; built data preprocessing pipelines and supervised/unsupervised models using Scikit-learn, TensorFlow, and Keras. Developed classification models for medical imaging tasks; tuned Random Forest, Logistic Regression, and SVM; built entry-level deep learning models. Implemented automated evaluation, reproducibility, and documentation; collaborated with senior engineers; contributed to anomaly detection to improve data quality; produced visualizations; maintained version control with Git; followed documentation; contributed to experiment tracking.

Education

Masters in Data Analytics at Indiana Wesleyan University
January 11, 2030 - September 9, 2025
Bachelors in Computer Science at Jawaharlal Nehru Technological University
January 11, 2030 - September 9, 2025

Qualifications

Add your qualifications or awards here.

Industry Experience

Financial Services, Healthcare, Software & Internet, Professional Services, Media & Entertainment, Education