Feb 2025 – Apr 2025 · 2 mos · Bangalore Urban · On-site

• Building Enterprise AI at scale -- document understanding, question answering, hybrid-search, summarizing for organizations. I'm overseeing the Engineering development in the startup.
• https://brahmasumm.com/
• Responsible for
• Owning the end client requirements and deliverables.
• Building RAG pipelines to process documents of various file formats of organizations.
• Improving the inference speed and response quality of the AI responses.
• Hiring top-quality engineers, and managing them.
• Working closely with the CEO for planning the company's priorities.
• Currently handling two major clients -
• A leading Research lab in the US (Lawrence Berkeley National Lab), using Brahmasumm to summarize their Research related documents. Deployed AI software services on-prem LLM for their IP data protection. The Research Lab is using Brahmasumm for summarising their Research related PLM documents, finding diff in their versioning, and asking questions to their PLM documents to get Perplexity-styled response with citations.
• https://www.lbl.gov/research/
• https://crd.lbl.gov/
• https://www2.lbl.gov/Science-Articles/Archive/new-elements-here.html
• A manufacturing company ATMUS (NYSE: ATMU) with many manufacturing branches, who are using our AI product to feed their industrial process PLM documents and machinery lifecycle maintenance information documents and get answers to Technical questions about maintenance of the machines.

Jul 2022 – Apr 2023 · 9 mos · Sunnyvale, California, United States · Hybrid

• Cloud Technologies Team
• Working on automation enabling data-driven Customer Insights and analysis into Cloud Technologies usage happening at Apple.
• Used Design Patterns, inheritance using classes extensively in code for extensibility to new usecases.
• Deployed services within Kubernetes containers, optimizing resource.

Mar 2020 – Jul 2022 · 2 yrs 4 mos · Sunnyvale, California, United States · Hybrid

• Google Cloud AI - Cluster Planning - Unified Fulfillment Optimization
• Google's compute resource planning and optimization systems team responsible for developing the software systems for forecasting, ordering, planning and provisioning of compute, hardware and network for Google's Data centers.
• Created automated software workflow for installation and decommission of machine fleet and related inventories by Data center Operations workers in Google Datacenters.
• Created automated workflow to enable IPv4 usage for Top-of-the-rack for machine fleet.
• Worked with cross-functional teams to deliver important projects, collaborating with stakeholders from different departments.

Oct 2019 – Mar 2020 · 5 mos · San Francisco Bay Area

• Automating medical coding with Machine Learning (NLP).
• http://fathomhealth.co/
• Implemented Optical Character Recognition of ~900K Health Records HIPAA Documents of a Medical provider and parsing the Text output to feed into downstream Spark / Big Query for Machine Learning Training, and verification script. Added 3+ data flow processes in DAG based pipeline implemented in Apache Airflow in the Health-Tech AI startup in San Francisco.
• https://blogs.nvidia.com/blog/2019/09/12/fathom-ai-medical-coding/
• Designed and implemented an EFK (Elasticsearch, Fluentd, Kibana) stack to collect, store, and analyze log data, improving visibility and troubleshooting system issues.

Jan 2019 – May 2019 · 4 mos

• Deep Learning course - Graduate Teaching Assistant, under Professor Zsolt Kira https://www.cc.gatech.edu/~zk15/
• https://www.cc.gatech.edu/classes/AY2019/cs7643_spring/
• Assisting Graduate students by answering their questions in Deep Learning by conducting Office hours and in online forum.
• Assisting Professor related to conducting the course.
• Created GPU Cloud environment for students to run Projects and Assignments.
• Created Deep Learning Contest in EvalAI platform for students to compete on Accuracy for Assignments.
• Corrected and grading graduate students' course work answer submissions.

Aug 2018 – Dec 2018 · 4 mos

• Registration and Fusion of 3D Point Cloud LIDAR Data with 2D Camera Data obtained from Georgia Tech's Device mounted Van, for assessing accuracy of Transportation Infrastructure detection (Traffic Signs, Traffic Light, Lamp Posts, etc).
• Under Professor James Tsai https://ce.gatech.edu/people/Faculty/1001/overview
• Technical Evaluation of LIDAR products in the market for recommendation to replace LIDAR device based on requirements for assessing Transportation Infrastructure by the Device Mounted Van.

May 2018 – Aug 2018 · 3 mos · Bangalore

• Working on building Offline natural conversation engine from scratch for the humanoid robot for various contexts - product Recommendation, Movie Recommendation with RASA NLU + RASA Core, moving away from Google Dialogflow for speech.
• Training Machine Learning models on NVIDIA Jetson TX2 for Vision for the Humanoid Robot.
• Created Alexa Skills with Alexa Skill Kit and Alexa SDK for Recommendations using Speech Conversation for the Robot.

Jun 2014 – Jun 2017 · 3 yrs · Palo Alto · On-site

• Worked on the Merchant Onboarding and Deal Creation team, supporting thousands of merchants in self-service deal creation. Contributed to key features like Card Linked Offers deal flow, redemption windows, blackout dates, and the Fine Print Service. My responsibilities spanned front-end (Angular.JS), back-end (Ruby on Rails), API integrations, automated testing, and documentation.
• Served as the point of contact for deployments across various merchant tools and services, including Fine Print and Contract Services. Built Splunk dashboards for visualization and set up Nagios alerts for monitoring key metrics.
• I contributed to the Image Asset Management Project, improving image discovery and management for deal content designers and editors, with a focus on language localization, keyword management, and permissions.
• Worked on Groupon’s Deal Creation Tool, which supports thousands of sales representatives and merchants, handling front-end, back-end, API integrations, automated testing, and documentation.

Apr 2012 – Jun 2012 · 2 mos · Bengaluru Area, India

• Summer Internship at DARE, DRDO Bangalore
• Analysed Web and network security inside DARE, DRDO against web and network attacks like SQL Injection, XSS Cross side scripting, DDOS attacks, etc.
• Suggested and implemented some improvements in security and submitted a report.