# Kranthi Kode > Staff Engineer at Stripe Location: San Francisco Bay Area, United States Profile: https://flows.cv/kranthi I build large scale AI / Machine Learning based distributed systems. I enjoy taking on hard technical challenges and worked on many impactful projects over the last 18 years. Previously at Pricing & Incentives at Uber, Search at eBay, Advertising at Microsoft, Display Ads at Yahoo! ## Work Experience ### Staff Engineer @ Stripe Jan 2021 – Present | San Francisco Bay Area Data Engineering Monetization / Revenue Platform ### Staff Engineer @ Uber Jan 2019 – Jan 2021 | San Francisco Bay Area Incentive Allocation Platform - how to optimally allocate incentives across the world, to balance future supply and demand in Uber's marketplace. Involved data engineering, machine learning, and optimization. Tech: Spark, Hive, Presto, Python DS stack (pandas, NumPy, etc.) ### Senior Staff Engineer @ eBay Jan 2016 – Jan 2019 | San Francisco Bay Area Architect for ebay.com next-gen experience's Search, Browse and Listing platforms (Backend). I joined an organization that was started with the goal of modernizing eBay's tech stack. We adopted state-of-the-art ML technologies from across the industry and applied them in e-commerce space to improve online shopping experience. - Cloud based stack leveraging many open source technologies: TensorFlow, Spark, Docker, Kubernetes, Play Framework (Scala), etc. - Streaming architecture with near real time pipelines keeping the Search index up-to-date. - Selection and ranking powered by deep learning models: semantic vectors for relevance, category prediction and NER for filtering and ranking, click prediction for re-ranking, etc. - The new platform, built from scratch in 2 years by 60 engineers, is 15x faster and resulted in 7x conversions compared to old stack. - Along with traditional search experience, the platform also supports eBay's chatbots on FB Messenger (eBay ShopBot) and Google Assistant. ### Senior Dev Lead @ Microsoft Jan 2015 – Jan 2016 | Sunnyvale As member of Architecture team, I led high-impact broad initiatives in a number of key product areas. Windows - Ranking service to replace the rules engine in Windows Engagement and Monetization System. AOL Transition - Led the creative migration track as part of transitioning Microsoft’s display ads to AOL. MSN As part of migrating MSN website to a new platform, - Implemented ad size prediction algorithm that helped prevent 900 potential incidents by detecting ad size assignment mistakes. In addition, it was used for pre-allocating correct sized ad containers on MSN, improving user experience. - Worked on a new BI product that reduced monitoring cadence from daily to hourly during MSN platform migration. - I also worked on MSN ad performance improvement initiative on the new platform. ### Senior Software Developer @ Microsoft Jan 2014 – Jan 2015 | Sunnyvale I played a critical role in architectural redesign of Bing's Product Ads. Bing Product Ads - Designed and built Selection and Ranking Server, a high performance c++ distributed server with load balancing, configurable protocols, watchdog, built-in logging, monitoring and metrics, test client, unit and component testing frameworks, scripts to aid deployment, etc. - Pipeline to ensure data quality of Product Ads. With 98% accuracy, the Judgment Engine algorithm I created dramatically reduced Bounce Rate / Quick Back Rate on Bing, improving user experience - Performed analysis on Product Ads Ad Selection, to find opportunities to improve the selection models. Hackathons - Demo'ed custom alerting features on Cortana. This hack won us first prize in the hackathon. These features have been adopted by Cortana team and were launched in production. - Demo'ed location based answering system on Cortana leveraging Product Ads. This hack won us third prize in the hackathon. ### Software Developer II @ Microsoft Jan 2013 – Jan 2014 | Sunnyvale XBOX - Built a mechanism to enable web ad demand on Xbox. The solution involved real-time transformation of 3rd party ad payload to Xbox compatible format. - Built shopping experience on Xbox using product ads. ### Co-Founder @ ProductPlay Inc. Jan 2013 – Jan 2016 | San Francisco Bay Area • ProductPlay algorithmically curates user generated video content at scale. These video reviews are then added to e-commerce web pages through our APIs, to increase user engagement and conversions. • Worked with major retailers such as Walmart, TheNorthFace, Electrolux, Macy’s, Kohls to integrate ProductPlay’s video content. A/B tests showed significant increase in user engagement and conversions in many categories. • Built a 5-person engineering team, designed the architecture and defined the technical road map. ### Co-Founder @ Odeon Jan 2011 – Jan 2014 | San Francisco Bay Area • Developed a suite of e-commerce iOS apps - StyleHer, DealRack, PetShop and HomeCandy. DealRack was ranked one of the top shopping apps by Apple in 2012. • Built an engineering team in India. Designed a single platform that supported features in all the apps such as Search and Browse. ### Software Engineer II @ Yahoo Jan 2012 – Jan 2013 | Sunnyvale I worked in Display Advertising, which was responsible for roughly half of Yahoo's total revenue. I spent time in both guaranteed and programmatic (RTB) advertising areas. I worked closely with researchers from Yahoo Labs to create Machine Learning model based services. I also worked on RightMedia ad server. - Developed model based services with config driven A/B testing of new models. These services support continuous experimentation through modeling innovations with minimal code changes. Models are trained on Hadoop clusters in offline mode and are pushed to production boxes periodically. - Designed and led the development of a number of broad features on RMX Ad Server. - Performance Engineering: Improved scalability and latency aspects of the Ad Server that serves ~10 billion impressions per day. - Mentored new hires through architectural discussions, debug sessions, code reviews, etc. - System level debugging ### Software Engineer @ Yahoo Jan 2010 – Jan 2012 | Sunnyvale I worked in a team called Unified Marketplace. We built services to enable federation between Guaranteed (Premium) and RTB advertising stacks. - Developed highly scalable, low latency distributed services (<10ms at 10,000 RPS per node) that are heavily used by Guaranteed and RTB ad servers. - Developed a data pipeline that uses Hadoop map-reduce (Apache Pig and Perl scripts) to process terabytes of data to provide forecasts for downstream services. - Implemented diagnostic modules and used profiling tools to find and fix performance bottlenecks. Improved supported throughput of a service by 400% using one such module, for example. - As intern (June 2010 - September 2010), designed and implemented a model for assessing the performance of third party ads. This work resulted in a patent. ### Research Assistant @ Stanford University Jan 2007 – Jan 2011 Some of the research projects I worked on: - Ontology Based Search: Developed a framework for carrying out search on databases like Pubmed using ontologies. - Quantitative Unmixing: Developed alternative algorithm to least squares (incorporating Optimization) for applications in nano bio technology. - PIDO: Worked on developing a platform to integrate CAD and analysis tools. - Iterative SVD: On-the-fly computation of reduced-order bases by iterative update of SVD. - A machine learning approach to address false positives in active structural health monitoring. - Implementation and Performance Studies of Multilevel k-Way Partitioning of Graphs. ### Founder @ SwipeIt Jan 2009 – Jan 2010 | San Francisco Bay Area • SwipeIt is one of the first iOS apps with swipe keyboard. With over 10,000 downloads a day, it was ranked #1 app by Apple in Europe for two weeks after launch and it continued to be in top 10 for several weeks. • Developed the ML algorithm to predict the word from swipe gesture. Built the iOS app with notes, messaging, and mail functionality. Monetized the app with iAds. ### Design Engineer @ NTPC Jan 2005 – Jan 2007 ### Engineer @ Gammon India Ltd Jan 2004 – Jan 2005 ### Summer Intern @ Remote Sensing Instruments Jan 2003 – Jan 2003 | Hyderabad Area, India ### Summer Intern @ ERDAS Jan 2002 – Jan 2002 ## Education ### MS in Computational and Mathematical Engineering Stanford University ### MS in Structural Engineering and Geomechanics Stanford University ### Online Certificate Program in Leadership and Culture Harvard Business School Executive Education ### B.Tech. in Civil Engineering National Institute of Technology Warangal ## Contact & Social - LinkedIn: https://linkedin.com/in/kranthikode --- Source: https://flows.cv/kranthi JSON Resume: https://flows.cv/kranthi/resume.json Last updated: 2026-04-12