• Developed several RAG (Retrieval Augmented Generation) applications: one for content based item (recipe) recommendations and summary, another for entity matching (recipe ingredients and recipes) on web scraped data. Designed prompts (prompt engineering) in some applications.

• Developed and implemented novel machine learning based scoring algorithms, drafted and filed a provisional & non-provisional US patent. designed and implemented the algo. in a complex backend and exposed it via RESTful APIs.

• Developed a react.js based complex PWA application utilizing the above Restful endpoints and the following search system.

• Developing a semantic image search feature based on embeddings to allow object identification in videos and search based on the set of objects identified.

• Hired and led a cross functional team of two engineers, one marketer and one UX engineer for growth by exposing certain functionalities of product per product-SEO strategy. Improved subscription conversion rate by 4x in 6 months.

• Hired and led a separate 3 person engineering team to deliver a complex compute service exposed via RESTful APIs. This backend service is tied to the SPA and PWA mentioned above.

• Worked with an engineer to set up a web scraper and parser in python. This scraper, run as a cron job, automates content addition to the website. This removed stale links and led to zero 404s and improved the organic SEO traffic 23% over trend line.

• Worked alongside a product manager to source and conduct customer interviews to improve understanding of the problems of prospective customers for our novel product.

• Worked with co-founder to perform market research and market sizing. Devised scenarios for the go-to market strategy and worked with the marketing team to launch the first product in a select market.

• Designed and implemented several data pipelines for processing of financial data using Kafka and Java applications.

• Transitioned a legacy data pipeline application to a java/elastic search/mongoDB stack including development and regression testing.

• Performed troubleshooting and root cause analysis of production bugs for several products in a product suite.

• Mentored and managed a team of 6 engineers. Improved delivery timelines of projects undertaken by the team. Improved quality of work delivered as measured by production bugs and downtimes.

• Automated several ETL processes using python which led to reduction in errors and better throughput.

• Led conversion of the group's flagship product offering to a free-trial model. Sales and lead generation improved by 3X and 12X respectively.

• Designed and developed a framework for retrofitting legacy applications with feature toggling. This greatly improved the ability of engineering and devops team to roll out new features for production testing and deployment, and perform A/B testing. It also enabled the sales team with the ability to offer variously featured and customized products at several price points.

• Designed and developed prototypes for attaching and managing remotely stored and versioned design files to the group's flagship PLM product. Success of this prototype was followed by a strategic change in the group's product offerings.

• Debugged and suggested a fix for a significant and critical bug in a logging library used across Autodesk that performed incorrect logging in race conditions. The result was an improvement in accuracy of reporting metrics.

• Designed and developed several critical features for improved user experience such as adding the ability to delegate work and escalate PLM responsibilities.

• Architected a system to match products against external entities.

• Designed a large scale data gathering and data analysis system. Developed the core pieces. Directed developers and quality engineers towards implementation, testing and deployment.

• Wrote map-reduce jobs in Hadoop to process the crawled pages.

• Engineered machine learning based matching technology to perform entity match.

• Automated collection of pricing information that was used as a factor for product search ranking.

• Discover deals among offers based on community pricing.

• Developed machine learning based models of user reviews for quality classification.

• Improved site conversion significantly by optimizing ranking of search results.

• Delivered a large scale solution to generate and manage the quality of ads for Search Engine Marketing (SEM) campaigns.

• Developed back-end for personalized multi-channel marketing campaigns

• Managed infrastructure for data collection and inference computation for search optimization