Worked with Microservices team at IBM Quantum cloud, on backend and API development of software stack that connects the Qiskit and IBM quantum website users to the quantum hardware

• Developed software stack using Javascript/Typescript and Node.js

• Integrated databases such as MongoDB and Redis

• Utilized Mocha and Jest for testing new functionalities

• Gained experience in Quantum Computing research

• Learned about superconducting qubits, and quantum software architecture

Web application that solves user frustration and time consumption when applying to jobs, by utilizing user’s skillset (education, experience, skills & project) to search for jobs and create a dynamic resume tailored to job

• Engineered job scraping, skillset/job sorting functionalities with Python, Flask

• Utilized ReactJs for designing user sign-in/up, onboarding, and job search/listing UI

• Maintained user pool using AWS Cognito, and AWS RDS for user data

• Deployed backend Docker images on AWS EC2 and frontend on AWS S3

Using the webcam it identifies different faces and displays the name of each person in the video in real-time.

• Used KNN algorithm for training the model and classifying faces

• Integrated other libraries such as OpenCV, face_recognition, and sci-kit learn

• Model achieved an accuracy of 0.93

Web application for summarizing a video/document into a smaller video or document

of 20% of its original length with additional notes on important keywords.

• Implemented ​microservice architecture​ for sign-in/sign-up, transcript/video processing, and video editing services

• Built each service as a ​RESTful​ ​API​ using ​React​, ​Python, ​and ​Flask

• Utilized​ API Gateway​ for user authentication, authorization, and request routing

• Encapsulated microservices using ​Docker ​for deploying in ​AWS EC2

• Worked with other technologies such as ​AWS Lambda​, ​S3​, ​Springboot​, and ​Jenkins