Hey! I'm Vikram, a Computer Science graduate from UWaterloo.
Feel free to learn more about me!
I graduated with a major in Computer Science from the University of Waterloo after completing internships at various companies like Redfin, Scribd and Flipp.
I am currently working at Redfin as a Software Engineer 1, building software that decides the value of homes across the US!
As a software engineer, my goal is to work for companies where I can challenge myself everyday, gain exposure to various technologies, and grow as a developer.
I’ve worked with many technologies throughout my internship roles and coursework, and am always striving to improve these skills everyday!
Here are a few of the technologies that I have worked with:
- Python
- Java
- JavaScript/HTML/CSS
- Ruby
- TypeScript
- C/C++
- C#
- Ruby on Rails
- Spring
- React
- Ionic Framework
- Angular
- ASP.NET
- MySQL
- PostgreSQL
- SQL Server
- Oracle
- AWS S3
- Amazon RDS
- Git
- Postman
- Building software that determines property valuation across the US
- Built a performant and scalable library to lay the groundwork for engineers to efficiently prototype and implement ensemble machine learning models
- Independently designed and developed a feature to improve the accuracy of closing costs on Redfin's iBuying contracts by thousands of dollars
- Reduced payment collection pipeline run time by 96%, by identifying and removing bottlenecks in database queries, using Ruby on Rails and MySQL
- Built a logging system from scratch to track over 1 million user accounts, for early detection of account-related suspicious activity
- Improved user satisfaction by 12%, by finding and addressing flaws in the promo code processing workflow
- Maintained Flipp’s monolith FAdmin web app that powers Flipp's platform by processing over 2M products/month using Ruby on Rails and MySQL
- Developed robust web scrapers for various retailer websites to scrape vital product information that would be consumed by millions of users
- Automated ingestion and sorting of digital flyer data from retailers for timely processing on FAdmin using Ruby and AWS S3
- Independently built, tested and deployed features for a business card scanner app with 1000+ users using Ionic Framework, Angular and TypeScript
- Improved processing time on high-resolution images by 48% by integrating image compression into the pipeline
- Significantly enhanced user experience by implementing authentication token renewal using Azure Active Directory
- Developed and shipped RESTful APIs that interact with government systems to validate business registration data using ASP.NET (C#) and SQL Server
- Utilized Postman for regression testing of the APIs
- Streamlined trader operations on internal web app by developing trader requested features using ASP.NET (C#), Oracle database and SQL Server
A visualization tool for various pathfinding algorithms such as Dijkstra's, A* (A-Star), Greedy Best-First Search and more!
A playable version of FlappyBird that has an integrated self-learning AI player. The AI is created using NEAT-Python library which uses an evolutionary algorithm to incrementally generate neural networks that gradually get better at playing (as shown in the gif above).
A web application that serves as an image gallery for images stored on the cloud. Uses Google Cloud's Vision API to label images, which allows for querying of images based on content or another image.
A POC smart web scrapper built as part of a hackathon that uses a neural network pre-trained to identify certain type of text. This neural network was used to identify relevant information and scrape it out of web pages instead of using XPath (a query language that selects elements on an HTML page, commonly used in web scrapping), which is prone to breaking if the UI of the web page changes.