Patidar Santosh
About Patidar Santosh
Patidar Santosh is a Senior Machine Learning Engineer at General Mills in India with extensive experience in deploying machine learning models on edge devices and managing AI architecture on AWS.
Title
Patidar Santosh holds the position of Senior Machine Learning Engineer at General Mills in India.
Previous Experience at BitByte Software Technology
From 2018 to 2021, Patidar Santosh worked as a Machine Learning Engineer at BitByte Software Technology in Indore Area, India. During this time, he focused on deploying machine learning models and improving their performance.
Python Developer at Engineer Master Solutions Pvt. Ltd.
Patidar Santosh served as a Python Developer at Engineer Master Solutions Pvt. Ltd. from 2017 to 2018 in Indore Area, India. Here, he utilized Python for various development projects, enhancing software functionalities and performance.
Education and Expertise
Patidar Santosh earned his Bachelor's degree in Electronics & TeleCommunication from Rajiv Gandhi Prodyogiki Vishwavidyalaya, where he studied from 2010 to 2014. He is proficient in multiple programming languages including C, C++, Python, Node.js, JavaScript, and TypeScript. His expertise spans AI architecture on AWS, Kubernetes infrastructure management, deep learning algorithms, and model compression techniques for edge devices.
Experience with Compilers and Model Optimization Tools
Patidar Santosh has hands-on experience with various compilers and model optimization tools such as Clang, NNVM, TVM, GLOW, VTA, Ngarph, XLA, MLIR, GCC, MSVC, QUIL, QUOB, and TensorRT. This expertise enables him to optimize machine learning models for better performance and efficiency.
Background in Web Backend and Embedded Systems
Patidar Santosh's early career included positions as a Web Backend Developer at Linkites Infotech Pvt Ltd (2015-2016) and as an Embedded System Engineer at ROBOTRONIX ENGINEERING TECH PRIVATE LIMITED (2014-2015) in Indore Area, India. These roles provided a strong foundation in both web technologies and embedded systems.
Quantum Computing and AI Model Deployment on Edge Devices
Patidar Santosh is actively learning and working with quantum computing frameworks such as Cirq, Forest, and Ocean (Leap). He also specializes in deploying machine learning models on edge devices, and employs model compression techniques including quantization, pruning, and distillation to optimize models for such devices.