About

Chakri M. is a full-stack Computer Vision Engineer with over 5 years of relevant experience in developing CV algorithms to solve business problems at a production scale. He has contributed to the entire computer vision product development life-cycle from conception to productionization, for both edge and cloud. Chakri's skills include model prototyping and evaluation using Python, Tensorflow, Keras, Pytorch, and Scikit-Learn Suite. Additionally, he is experienced in model optimization and finetuning for given hardware such as Nvidia-GPUs, Tensorrt, pyMNN, and TVM Compiler Stack. He is also well-versed in model deployment on engineering infrastructure using Flask, REST APIs, Docker, DeepStream, Triton Inference Server, and FastAPI. Chakri has a strong foundation in Machine Learning R&D from startup work experiences where he developed state-of-the-art algorithms in Deep Learning and Computer Vision. He has had the opportunity to apply ideas from academic research in an industrial environment. Chakri's past experience includes working as a Computer Vision Solutions Engineer at Nearbuzz and as a Research Fellow at LVPEI Center for Innovation where he developed a real-time medical image processing algorithm using GPU and machine learning algorithms for prediction that runs completely on single board computer, Odroid-XU4. Chakri holds a Bachelor's Degree in Electronics and Communications Engineering from RGUKT. His tech stack includes Computer Vision, Deep Learning, Research Scientist, Keras, Scikit, ML, Python, Docker, Tensorflow, Flask, Pytorch, infra, and Image Processing.