Aditya Raj

Summary

Currently, I work as a Data Engineering Intern at George Mason University, where I design and maintain scalable data pipelines, work with structured and unstructured datasets, and support analytics and downstream modeling workflows. This role has strengthened my understanding of data quality, feature readiness, and system reliability—critical foundations for deploying machine learning models in real-world environments.

Previously, I have worked as a Research Engineer at Electro Tech Systems, applying machine learning techniques using Python, Scikit-learn, and TensorFlow for time-series analysis, anomaly detection, and predictive modeling on sensor and power-system data. I also have professional experience in data analytics, cloud infrastructure, and DevOps, including AWS, CI/CD pipelines, and containerized deployments, enabling me to bridge the gap between ML research and production systems.

As a DevOps Engineer Intern at Xebia, I designed CI/CD pipelines, containerized applications with Docker, and contributed to a full-stack hotel reservation system. This strengthened my understanding of integrating AI with scalable infrastructure.

My long-term goal is to transition into Machine Learning Engineer or Applied ML Research roles, where I can build robust, scalable, and interpretable AI systems that solve real-world problems.