Jan 2023 – Present · 3 yrs 2 mos · Sunnyvale, CA

• Working on Graph Algorithm and Analytics initiative for LinkedIn and Microsoft Azure.
• Working to bring suite of analytics and algorithmic capabilities such as path finding, community detection on really large scale graphs
• Data Ingestion for Graph Database @ LinkedIn aka Liquid.
• Improved ingestion throughput by removing memory and CPU bottlenecks
• Developed quota and throttling mechanisms for various data verticals part of the Graph database
• Contributed to Kafka Opensource to introduce Java memory pools to improve garbage collection efficiency
• Improved performance and reliability of index bootstrap by eliminating the multi-region datacenter copies by 90%
• Served as TL for the data ingestion leading cross company initiatives to bring Graph technology to Microsoft

Jun 2020 – Dec 2022 · 2 yrs 6 mos · Sunnyvale, CA

• Data Infrastructure / Graph Database Team
• I work on Liquid, an in-memory distributed graph database designed to serve declarative queries at high throughput and with low latency on LinkedIn’s Economic Graph. Liquid is a secondary global index consuming updates from different data verticals at LinkedIn in near realtime manner.
• Liquid powers various social graph canvases ranging from basic 2nd and 3rd degree connections to things like finding the people who can refer you to a job you are looking at, finding the people who went to same school/company as you or who reacted to your post and many more.

Jun 2018 – Jun 2020 · 2 yrs · Greater Seattle Area

• I worked on AI Inferencing Platform, which enables intelligent scenarios across the Office 365 email, documents, and Sharepoint websites. I focussed for the platform's online infrastructure and NLP stack.
• I contributed to the Office 365 Search team by enhancing machine learning infrastructure for email processing and document summarization. My work focused on real-time entity extraction and document summarization, which powered features like search autocomplete index, reply autosuggestions, and user personalization.
• Moreover, I contributed towards development of generic the ML workflow engines, which empowered data scientists and ML engineers to ship represent their ML pipelines in production.

Jan 2018 – May 2018 · 4 mos

• TA for 18-731 Network Security
• http://users.ece.cmu.edu/~vsekar/Teaching/Spring18/18731/

Oct 2016 – May 2017 · 7 mos

• Worked under Prof. Nicolas Christin and Prof. Lujo Bauer to investigate and mitigate credential steal-
• ing attacks against Windows Services Architecture sponsored by NATO. Designed a threat model and
• steps to prevent them by using Trusted Platform Module and Managed service accounts.

May 2017 – Aug 2017 · 3 mos · Greater Seattle Area

• I successfully contributed to NVIDIA's GPU Cloud by enhancing the training infrastructure for deep learning applications.
• Developed a dynamic job scheduler that improved the efficiency of container-based job management across NVIDIA DGX machines.
• Streamlined end-to-end status propagation for machine learning datasets, ensuring accurate monitoring and logging.
• Implemented robust security protocols for both the job scheduler and Docker images, enhancing overall system security.

Sep 2014 – Jul 2016 · 1 yr 10 mos · Bengaluru Area, India

• Part of Symantec Validation and Identity Protection (VIP)
• Worked for creating Single Sign-on based integration for OTP based authentication for Active Directory Federation Services (ADFS), Microsoft Credential Provider, Epic Authentication Systems
• Created from scratch a Windows Hello like authentication addon with help of Bluetooth LE and
• TouchID on iPhone.
• Find out more at https://vip.symantec.com/

Jun 2014 – Aug 2014 · 2 mos · Chennai Area, India