Developed a microservice with a frontend to configure SLA policies and a backend to facilitate requests and send notifications; unit tests to validate interactions between the two components. Notifies 1,000,000+ SLA requests per day
Developed a fully trained NLP model that has been deployed / hosted on AWS EC2; currently, groups 1000+ issues a day on Jira to save time for end users
Developed a task management mobile app that facilitates task assignment and tracking, incorporates user authentication, including data models, RESTful APIs, and front-end components, all managed by a full-stack team
Built a software that detected anomalies in user entry data to help Prove find false identities and inconsistencies in customer endpoint usage faster
Developed a driver monitoring system for FF's vehicles to detect symptoms of drowsiness using computer vision and neural networks, increasing safety and responsibility on the road
Worked on APIs to modify the database for item lookup, cart, and order functionality for customers. The team created a web app for Attain to input new products and filter customer orders.
Built a cross-platform mobile application which digitizes contractors' sitewalks using a fast and intuitive interface while automatically saving updated property information
Engineered a social-networking mobile app to build personal connections based on similar music taste identified through the Spotify web API, enabling original music recommendations
Worked on rolling out several features such as revenue charts, custom navbars, and email lists for a platform for Instagram sellers to easily generate custom websites
Implemented a machine learning algorithm to measure student learning styles and created the backend for a groups feature to support online student success
Created a full-stack service that helped CENTRL visualize and organize it's customer data in order to assist them when identifying problems
A full-stack application where customers (public safety agencies) can view relevant usage data and analytics from incidents/exercises in an intuitive interface