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Work Experience
Software Developer
Cover Financial, Inc.• February 2020 - Present
• Working in the Internal Tooling team which focuses on discovering, designing and prototyping new solutions for internal teams to reduce toil and provide valuable engineering tools. • Collaborating with the Data Science team to create tools and scripts in Python to automate the ingestion and consolidation of operational data for insurance quotes and ratings. • Re-architecting and implementing an automated test framework written Ruby using plug-in architecture. • Had the opportunity to receive Practical Object-Oriented Design Course by Sandi Metz.
Software Engineer
Auriss Technologies• July 2017 - July 2019
o Worked for core engineering division of US-based Startup, Akitra, which is building Enterprise IoT Cybersecurity and Threat Analytics platform. o Job responsibilities span predominantly across two teams: 1. Cybersecurity and Threat Analytics team, and 2. Infrastructure and DevOps team. o Work in the Cybersecurity and Threat Analytics team largely consists of research into various forms of & tools for attacks and anomalies, design, and implementation of scalable Machine Learning applications to parse, analyze, and detect anomalies in network traffic data emanating from IoT devices. o The initial phase of work involved research & analysis into four core attack categories of DoS/DDoS, Probe, U2R (User to Root) and R2L (Remote to Local). o Based on the research, built automated attack tools employing Kali Linux, Mininet & python scripts to generate distinct attacks based on assorted configurations for the core attack categories and produced germinal datasets for machine learning models. o Built the first layer of analysis and detection tools in Python incorporating parameter tuned, out of the box algorithmsScikit-learn library (supervised and unsupervised), and training and testing them with curated, feature-engineered NetFlow and streaming network traffic data set. o Then worked on parameter learning and probability modules for static and dynamic Bayesian Network machine learning models from scratch in C++ to ingest, analyze and characterize IoT device network traffic. o Architected and developed Snort IDS based Smart Security Engine (SSE) written with pure C++ interface and integration of SSE into the Bayesian Network. o Lead the Infrastructure and DevOps team to Architect and Deploy the Ai3 solution using Docker and Kubernetes via Cloud (AWS, GCP) and on-premise automated deployment mechanisms. o Lead the Automated Decision Engine (ADE) team to use Planning, Scheduling and Constraint Programming in Computer Networks to help detects anomalies and take preventative actions.
Software Engineer
Sai Technologies • October 2014 - June 2017
o Used statistical models & pattern analysis on complex data sets from different business units of the company to extract associative, comparative, and predictive insights. o Performed data munging, cleaning, structuring and processing along the chain with the help of tools & technologies such as T-SQL, MongoDB, Python scripts (with numpy, scipy and pandas libraries), Microsoft Azure Machine Learning Studio. o Worked with market research and business development team to develop automated web scraper and data consolidator tool chest based Python, Scrapy, BeautifulSoup4, MongoDB and associated modules to help perform analytical studies on areas such as demand estimation and forecasting, opportunity assessment, and competitive analysis. o Extensively used Python with Machine Learning toolkits to map, analyze data extracts and to build predictive models. o Dealt with data retrieval, migration, and consolidation of both structured and unstructured data fromdiverse business units of the company such as retail, sales, inventory, accounting. For this effort architected and built diverse set of data ingestion & collector modules based on Python, SQLAlchemy ORM, Pandas, Regex, MySQL, and glued together with RabbitMQ communication layer. o Lead the team that worked on automated monitoring & control of inventory levels, production speed and product demand to determine reorder levels to ensure product availability and minimize inventory costs.
Co-Founder
FluxBand• March 2014 - October 2014
○ Worked on designing and developing the core technology and platform for FluxBand, which is an ambience sensing wearable device that helps characterize, analyze, and quantify the environment. FluxBand was a portfolio company of Plug-and-Play Ventures in Silicon Valley as part of their IoT Accelerator in collaboration with Bosch-Sensortec. ○ Developed and implemented algorithms for Predictive and Prescriptive Data Analytics for the data collected from the wearable device sensor suite and enabled it to be presented to the users in easy, quick digestible format. ○ On the hardware part of the stack built out prototypes and production PoC devices with embedded systems starting from barebone microcontroller, Arduino based systems to bespoke sensor suite on BeagleBoard platform, customized PCB units ○ Built out the connective layer with heterogeneous communication and protocol stack implementing technologies such as AMQP, MQTT, WebSockets, RESTful APIs and such enabling platform networking, control and orchestration ○ Machine learning models & data processing for Data Analytics module were designed and developed in Python and C/C++ code base depending on the hardware stack used and deployed accordingly. ○ Engaged with customer and process side of the startup with continuous validation process, A/B testing and feedback-iterative product development as a part of lean startup methodology
Engineering Lead
USC Annenberg Innovation Lab• June 2012 - July 2013
Startup-in-residence. ○ Worked as Engineering Lead for Theia: Handheld Braille Aid which is a piece of assistive technology that provides a seamless e-reading experience for people with visual impairments and was incubated as Startup-in-Residence in the USC Annenberg Innovation Lab ○ Worked on and led the team to design and develop various distinct facets of the technology such as embedded systems core, onboard OCR & image processing technology, micro-electromechanical systems powering Braille system, device form factor, etc. ○ Part of the work also entailed interviewing, recruiting and managing an interdisciplinary engineering team and facilitate seamless coordination with other departments
Education
Georgia Institute of Technology, Atlanta
Computer Science, MS• August 2019 - Present
Currently pursuing OMSCS with a specialization in Computing Systems
University of Southern California (USC), Los Angeles
Electrical Engineering, MS• September 2011 - May 2013
Anna University
Electronics and Communication Engineering, BE• September 2007 - April 2011