About

Prakash S is a Software Engineer at Amazon, with a solid foundation in coding, testing, code reviews, and other software engineering practices. He has an interdisciplinary background in Mechatronics engineering, primarily focused on Computer Vision and Python. He has a keen interest in software engineering, information theory, digital control, and electromechanical control systems. Prakash enjoys building automation projects and developing software. Currently, Prakash is working as a SDE in Alexa communication team at Amazon. In the past, he worked as a software engineer at GKFIT and a computer vision engineer at Bigthinx. In 2018, he co-founded an e-commerce platform ClothX (now archived). Prakash has earned his undergraduate degree in Mechatronics engineering from Anna University in 2019. At GKFIT, Prakash was responsible for developing the backend and deep learning components of the core software product, as well as other relevant integration of new technologies. He designed and implemented a Rest API for Deep Learning model inference with network throughput up to 3000 requests per second using C++, TensorFlow, and gRPC. He developed backend microservices for internal custom dataset management tools using Flask and MongoDB, deployed on Gcloud. Prakash also wrote test suites and set up CI/CD pipelines for the application production release and exceeded requirements in every stage. At Bigthinx, Prakash was responsible for developing and executing the Artificial Intelligence of Bigthinx products using Computer Vision, Machine Learning, Deep Learning, OpenCV, and other relevant frameworks, as well as integration of new technologies. He proposed and implemented process-based parallelism, which reduced the Image Processing server's latency by 60%. He also implemented ML detectors using C++ and deployed them on edge devices. Prakash developed GPU-accelerated Docker images to be used in production that enabled on-demand server scaling, thereby reducing the overall cost of the servers. He researched and prototyped techniques/algorithms for object detection and recognition and identified new problem areas and researched technical details to build innovative products and solutions. Prakash's tech stack includes Software Engineering, Computer Vision, test, Deep Learning, Backend, Python, Integration, CI/CD, TensorFlow, MongoDB, Microservices, Flask, ML, Web3, Object detection, OpenCV, Object Detection, Image Processing, and Docker. He has 2.36 years of relevant experience in the field.