SRIDHAR NANDIGAM

Machine Learning Engineer, Full-Stack Developer, Computer Science Student

Hello there! My name is Sridhar and I'm a CS student at UT Austin. I love to code and pretty much work on anything that looks cool.

Projects

My Website

My personal website to show off what I have learned and what I am learning. Kind of a glorified resume at the moment. Stay tuned.

Sustainabrand

Project we made for AlphaHacks to find all sustainable brand alternatives to big brand names with unethical or unsustainable business practices.

Flower Classifier

A simple classifier made with Pytorch to classify flowers using the model that the user inputs through the command prompt. Developed for the Udacity Machine Learning Nanodegree to grasp the fundamentals of data processing and neural networks.

Experience

Amazon Web Services

Software Development Engineer Intern - Redshift

(May 2023 - July 2023)

Developed CI/CD pipeline with Ruby to reduce deployment on-call time from 5 days to 2 days with automatic merging, integration testing, deployment, and rollbacks
Wrote end-to-end integration tests in Java for Redshift database cluster failure remediation functionalities and increasing coverage by 250%
Designed alarms to monitor performance of CI/CD pipeline and deployed software

CGN Global

Data Engineer Intern

(May 2021 - August 2022)

Used C# to retrieve data from API and merge into SQL Server database
Architected data solution for one of our top clients in an ETL staging server with SQL
Debugged and fixed data transform issues in production environment to avoid significantly impacting over 800 active users.
Collaborated in the design and build of data analytics platform
Designed tools to support provision of enterprise data for transactional reporting and dashboards

TWG Technologies

Machine Learning Engineer Intern

(May 2021 - July 2021)

Preprocessed and cleaned image dataset with OpenCV for training
Designed and integrated Pytorch image classification models with applications
Created object detection algorithm with Tensorflow API
Responsible for the designing and implementation scalable systems to properly integrate machine learning with AWS SageMaker
Explored and implemented MLOPs best practices

Biomedical AI Lab at UNT

Machine Learning Researcher

(June 2020 - December 2020)

Read in accelerometer data as x, y, and z coordinates from Android device to build dataset from the ground up
Cleaned and prepared data with Pandas and Numpy for training and testing
Developed LSTM model with Tensorflow to use coordinate data to recognize hand gestures
Co-authored book chapter on autoencoders, embeddings, and their applications