I'm Rita Kuo
Software Engineer
- Location Los Gatos, CA, USA
- E-mail ritakuo@gmail.com
Software developer with expertise in building capabilities and services for SaaS platforms. Experienced in design, implement, and support cloud-native payment services that process more than eight billion dollars a year.
Professional Skills
Work Experience
Intuit
Senior Software Engineer
Design, develop, and drive to release Intuit’s Next Generation Payment platform – set of REST microservices, JMS listener and publisher, and Quartz job built using SprinBoot, AWS, and Kubernetes. A unified platform that supports all payment methods, multiple countries and currencies, and integration with multiple payment service provider.
FICO
Lead Software Engineer
Develop, deploy, monitor and support Decision Management Platform, a large-scale distributed system that scales to hundreds of nodes, for both on-premise and cloud customers.
Raytheon Company
Senior Systems Engineer
Worked in the full life cycle of a large-scale military communication project: design, develop, integration, test, release, and maintain.
Education
AWS Certified Developer
M.S. Software Engineering Management
California State University, Fullerton
B.S. Electrical Engineering & Computer Engineering
University of California, Irvine
Projects
Auto Complete feature
Search functionality is one of the most important feature in web applications because it enhances user experiences by helping them to find the right content quickly and easily. The autocomplete feature (for example, Google suggestion) enhances the search functionality by providng suggestions for the user to choose from based on user input. This feature has been widely used in online shopping website and search engines. In this project, we simulate the auto complete feature of the search engine by building a language model from Donald Trump’s 2016 speeches. I chose Mr Trump's speech file because its file size (1MB). There are 4 steps to implement this feature: 1. Build the N-Gram library 2. Build the langauage model based on the N-Gram library 3. Predict the next phrase using MySQL
4. Front End Programming
Crowdfunding Platform for Students
• Developed a KickStarter-like web application supporting multi users, posts, and comments. • Integrated App with third party Parse server using MongoDB database and deployed on Heroku to validate user info and store user posts. • Integrated authentication and authorization feature to support login logout, using cookie session mongodb.
Netflix Movie Recommender System
• Implemented 3 Map Reduce algorithms for Item Collaborative filtering based on similarities between two movies. • Recommend new movies to user based on user’s historical movie rating. • Ran Map Reduce jobs on Hadoop on top of a Docker container.
Netflix Movie Recommender System
• Implemented 3 Map Reduce algorithms for Item Collaborative filtering based on similarities between two movies. • Recommend new movies to user based on user’s historical movie rating. • Ran Map Reduce jobs on Hadoop on top of a Docker container.
Analyze User location data on Cloudera Hadoop platform
• Generated random user location data using Python and connected to Amazon Simple Storage Service (S3). • Set up one master node and four slave nodes on Amazon Web Service (AWS) Elastic Compute Cloud (EC2). • Installed Cloudera Manager and Cloudera Distributed Hadoop (CDH). Wrote Map Reduce code to extract location data.
My Interests
- Bicycling
- Watch Movies
- Ski
- Shopping
- Reading
- Travel
Contact Me
- Location Los Gatos, CA, USA
- E-mail ritakuo@gmail.com