Orchestrated the development of asynchronous Tornado web server services, functioning as middleware that facilitated two-way communication between onsite hardware and the backend infrastructure, collecting telemetry data and enabling remote commands through RPC.

Configured and maintained key AWS services (EC2, Lambda, DynamoDB, S3, Kinesis) to power the entire platform solution.

Leveraged industry-leading tools such as DynamoDB, RabbitMQ, and Django framework to build and deliver a high-performance backend capable of persisting real-time streamed telemetry data seamlessly.

Pioneered a WebSocket server solution that delivered new features that successfully closed crucial business needs for live alerting, crucial to customers.

Designed and implemented scalable Django RESTful APIs utilizing Django REST Framework, providing applications with seamless backend connectivity.

Built an authenticated and secure multi-tenant system

Used Scrapy Framework to scrape data from a network of websites

Setup Google Cloud infrastructure to support scaling of inter-connected servers and services

Developed Machine Learning classifiers using sci-kit learn, one of which classified data based on category derived from scraped labeled data

Used Stanford CoreNLP to perform Natural Language Processing tasks on scraped data to be used in machine learning tasks

Build an in-house version of Amazon’s Mechanical Turk service using Django and AngularJS to provide a platform for human intelligence to annotate data that will be used for labeled machine learning tasks

Built several dashboards using D3 to measure scraped data and human intelligence

Used Django Rest Framework to create REST API endpoints and integrated with React SPA front-end

Developed many REST API endpoints using Django that provide Logically services