About

Rahul Solanki is a highly skilled Machine Learning Engineer with a passion for solving complex problems using Machine Learning, Deep Learning, and Computer Vision. Currently working at Amazon, he has a wealth of experience in the field, having spent 4.77 years working on a range of projects across various domains. Rahul's technical skills are extensive, including proficiency in C, C++, Python, TensorFlow, MATLAB, OpenCV, Javascript, and Nodejs. His expertise in Machine Learning, Deep Learning, and Computer Vision has been honed through his work on a diverse range of projects, including building an end-to-end action recognition pipeline with as little as 1 hour of video data, working on data labeling pipelines using AWS Sagemaker GroundTruth and MTurk, and developing object detection models to detect regions of interest for a visual inspection system. Prior to his current role at Amazon, Rahul worked as a Machine Learning Engineer at Landing AI, where he played a key role in reducing the inference time and memory footprint of the overall ML pipeline by about 20%. He also worked as a Deep Learning for Signal Processing Summer Intern at MathWorks, where he built a labeling tool for time series signals that was embedded into the signal analyzer toolbox in MATLAB. Rahul holds a Master of Science degree in Electrical and Computer Engineering from the Georgia Institute of Technology, where he focused on Masters in Electrical and Computer Engineering. He also holds a Bachelor of Technology degree in Electronics and Telecommunication Engineering from Veermata Jijabai Technological Institute. With a strong technical background and a passion for solving complex problems, Rahul is a valuable asset to any team working in the field of Machine Learning, Deep Learning, and Computer Vision.