Actively looking for full time opportunities in software development.
Interned at On Semiconductor and AWS AI .
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Experience
DevOps Fellow, Insight, San Francisco May 2020 – Jun 2020
• Created DevOps pipeline for databases by using Terraform, EKS,ECR, CircleCI ,SQLAlchemy and PostgreSQL to manage database from development to QA and from QA to production
• Implemented the migration of databases with traceability to database changes and ability to roll back by creating tests in dev, QA and production environments
Enterprise Applications Intern, ON Semiconductor, Phoenix Jan 2020 - May 2020
• Upgraded legacy warehouse management application into custom built application for ON semiconductor by using python, application based unit testing, and oracle sql database.
• Analyzed the relational data in warehouse management application for visualization and in order to generate system implementation metrics
SDE Intern, AWS AI, East Palo Alto Jun 2019 - Aug 2019
• Contributed to SageMaker Debugger tool, which helps to analyze tensor data created by machine learning models in order to improve performance and reduce training time for ML models
• Improved speed of fetching tensors by 2x for analyzing and debugging by indexing functionalities for S3 or local machine storage using python development for tensorflow and MXNet models
• Created code integration and deployment system to maintain code quality and update the team on any errors in integration of code by automated chime notification using AWS lambda,Codebuild and Cloudwatch
Drivedge Infosolutions, Pune, India: Web Development Intern June-July 2016
• Designed Project Management Portal which helps project manager to manage and distribute the resources among different project and tracks progress of each project and individual employee.
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Projects
ASU, Smart Gallery Android app : Mobile Computing August-Dec 2019
• Implemented offline module based on android ML kit to gather images in android device, generate and store labels for images and identify text
which can be used to search images.(technologies used: SQLite database, Android ML kit, Android studio)
ASU, Quora Insincere Questions Classifications: Statistical Machine Learning Jan-May 2019
• Processing textual data to make it useful for models. Implemented various traditional models like SVM, Logistic Regression etc.
• Implemented Text CNN model which created a neural network to learn from phrases instead of words and compared various models and analyzed
the results. (technologies used: Jupyter , Keras librabry, python, sklearn)
ASU, Recommender Systems using Netflix Data: Semantic Web Mining, Machine Learning Jan-May 2019
• Main idea is to suggest combinations of approaches for recommendation of movies based on data provided and also provide analysis of existing methodologies. technologies used: Keras librabry, python, sklearn, SageMaker)
ASU, Autoencoders: Fundamentals of Statistical Learning and Machine Learning July-Dec 2018
• Collaborated in a team of four to implement de-noising autoencoder without using TensorFlow and keras libraries and utilized different kinds
of noises and parameters for network to find best de-noising autoencoder, which removes noise efficiently by learning from
images in fashion-MNIST dataset. (language used: python)
ASU, Neural Networks: Fundamentals of Statistical Learning and Machine Learning July-Dec 2018
• Implemented binary neural network for the MNIST dataset, to identify numbers. Also implemented general multilayer neural network from scratch.
VIT, Data De-duplication: B. Tech Capstone Project Jan-May 2018
• Purpose of this project is to keep unique copy of a document for all users. Successfully utilized various mechanisms for the security of files such as encryption, key generation to grant access to files, hash check to detect corrupt files, ensured better performance using progressive methods to detect duplicates which are faster than traditional methods.(technologies used: java, SQLite)