As an Associate Machine Learning Engineer, I thrive on creating impactful, data-driven solutions using cutting-edge technologies. With a Master’s degree in Computer Science Engineering from Southern Illinois University and a background in DevOps, I am passionate about developing scalable machine learning models and automating processes to improve operational efficiency. My expertise spans end-to-end machine learning pipelines, from data extraction and transformation to model deployment. I have hands-on experience with tools like PyTorch, YOLOv5, and PySpark to create robust solutions in Computer Vision and MLOps. During my time as a Graduate Assistant, I specialized in Autonomous Vehicle simulations, leveraging Federated Learning and object detection models to enhance the precision of AV systems. My experiences working with cloud platforms like AWS and Azure, as well as implementing automation with Ansible, Terraform, and Docker, have strengthened my skills in both machine learning and system operations.I am committed to continuous learning and improvement, always looking for innovative ways to integrate machine learning into real-world applications. With a solid foundation in DevOps and a passion for operational excellence, I am eager to contribute to cutting-edge projects that drive the future of technology.