Jinesh Mehta

I am working as a Machine Learning Engineering Intern at Schneider Electric as part of the Digital Innovation and Technology team. My work over here includes developing Deep-RL-based models which are used for recommending databases to end-users using previous user interactions. My responsiblities over here also include designing and deploying end-to-end CICD pipelines for SE Intel Database Recommendation System. For this task, I use AWS services like S3, ECR, Lambda, Sagemaker StepFunctions, EventBridge & CodeBuild which helps achieve robust & seamless deployments.

I worked as a Senior Software Engineer where my responsiblities included leading development teams for simulation and analytical tools used in engineering aircraft engines focused on turbines, compressors and fans.

I was working on Natural Language Processing (NLP) and unsupervised machine learning problems in the context of density-based clustering. Along with NLP, we were also exploring some more applications using Deep Learning in real time systems.

I was part of a worldwide group of researchers led by Michael Bernstein in Stanford CS. The research direction of the group is to "Design the Next-Generation Crowdsourcing Platform" in the space of human-computer interaction exploring a self governed crowdsourcing marketplace designed to amplify trust in crowd work

I was part of development team which was working on a software called "Fracktory 2.0". This tool acts as a communicator between the server and the client. Major features of this update includes adding a cross platform desktop interface for enabling simpler wireless communication between a 3D printer and client. This helps reducing input parameters from the client's side