Feb 2023 – Nov 2023 · 9 mos

• Built a ML Platform for marketplaces to help them improve their revenue through better product ranking. Went through YC with this idea, drove the company to $50K ARR + $240K in sales commitments, and pivoted away from this product

Nov 2022 – Feb 2023 · 3 mos

• Built a tool to help onboard software engineers. Pivoted.

Nov 2021 – Dec 2022 · 1 yr 1 mo

• Founded the Search Engineering team at Gopuff. Our primary responsibility when I joined was to move off a 3rd party Search system and bring it in-house.
• We had a rudimentary Search system build using text-matching in Elasticsearch and a semantic ranking model capturing relevance and product quality. We supercharged this system with some sophisticated query understanding with BERT models, real-time ranking XGBoost models layered with business logic to overtake the vendor we were working with.
• We also built a new recommendations system capable of serving real-time personalized recommendations to users in <100ms.
• In addition to this, we expanded this system to be used across all product ranking and recommendation surfaces across Gopuff.
• The impact of this project is nearly 2 Million dollars in bottom line savings for the company, and >$20 million dollars of top line incremental revenue impact, as measured by A/B tests.
• In addition to my technical performance, I also manage an Engineering team that continually strives towards pushing the limits of Search and Gopuff.
• 1. Managed a team of 5 people and created foundational processes that weigh collaboration and productivity
• 2. Built a new ad-hoc requests process to help the team operate more efficiently with fewer distractions
• 3. Set up a new design review process in the team to facilitate farming for dissent and ensure engineering excellence
• 4. Led the team to deliver a few key foundational features such as Search Filters, Product Substitutions, etc.
• 5. Built out new processes that weigh product needs (tight feature estimation, dates on product delivery) and engineering needs (developer productivity, developer creativity and satisfaction, and growth)
• 6. Proposed, built, and delivered high quality ML Infrastructure being used across several teams at Gopuff
• 7. Leveraged the above infrastructure to deliver $20M+ of incremental revenue to the business through iterations on Relevance and Ranking projects

May 2021 – Oct 2021 · 5 mos

• Founded the Machine Learning Infrastructure team, with a focus on creating a robust Machine learning platform to be used across all departments at Faire. The primary focus of this team was to solve problems for search, and "platformize" them so the solution could be used by other teams.
• Examples of the areas of ownership for my team were:
• 1. The online and offline feature store
• 2. The model training pipeline, largely focusing on XGBoost models for low-latency predictions
• 3. Model monitoring systems including anomaly reports, prediction drift detection, real-time feature drift
• 4. A Real-time model inference system capable of making thousands of predictions with tens of thousands of features in <100ms, with single model inferences being measured as low as single-digit millisecond performance
• 5. Overall system health metrics (Online -> Latency, Accuracy, Memory, Real-time features, etc), (Offline -> MRR / NDCG over time, Search conversion over time, etc)
• Areas of my impact included:
• 1. Founding the team from ground up
• 2. Building out a career ladder for Machine Learning Engineers
• 3. Defining the job description for the role, including day-to-day responsibilities
• 4. Founding an Engineering-driven roadmap spanning several years of planned work to ensure the systems are able to scale with the company's hypergrowth, especially as the company transitioned from "moving fast and breaking things" to "moving fast, with quality in mind to serve our customers"
• 5. Managing and mentoring a small team to empower them to reach their true potential

Jan 2020 – May 2021 · 1 yr 4 mos

• Designed and built an online Feature Store for Faire, capable of
• retrieving tens of thousands of features for a particular user request
• in under 50ms
• 1. Architected Faire’s real-time ranking system that includes feature
• retrieval, online feature computation, model evaluation, and feature
• recording. The system scores hundreds of products and serves recommendations in under 100ms
• 2. Implemented an end-to-end monitoring and alerting framework for
• the real-time ranking system that allowed us to monitor system health and guarantee uptime
• 3. Optimized the online feature store with state-of-the-art serialization
• and compression scheme, reducing latency, storage, and memory usage by over 50%
• 4. Built the foundational “real-real time” feature generation system
• that tracked user session behaviour as they browsed our site to
• supercharged our machine learning models
• 5. Deployed a sophisticated multi-armed bandit scheme aimed to
• improve the experience of new brands on Faire. Improved new
• brand conversion by over 20%, a key company initiative at the time
• 6. Trained a brand new search real-time ranking model that improved
• the top line revenue of the company by 2%, translating to 10s of millions of revenue impact
• Read more about the system I designed and built here:
• https://craft.faire.com/building-faires-new-marketplace-ranking-infrastructure-a53bf938aba0
• https://craft.faire.com/real-time-ranking-at-faire-part-2-the-feature-store-3f1013d3fe5d

Nov 2016 – Jan 2020 · 3 yrs 2 mos · Greater Toronto Area, Canada

Jun 2015 – Sep 2016 · 1 yr 3 mos · San Francisco

Apr 2014 – Aug 2014 · 4 mos · San Francisco Bay Area

Sep 2013 – Dec 2013 · 3 mos · San Francisco Bay Area

Jan 2013 – Apr 2013 · 3 mos · Shelton, CT

• Working with Android and security algorithms to preserve user privacy.

Apr 2012 – Aug 2012 · 4 mos

• Worked in J2EE to develop various features for core Drivesync platform
• Wrote code in JSP, JavaScript, and CSS for front end changes
• Utilized Spring technologies for dependency injection
• Worked with Hibernate and HQL to manage Entity beans and DAOs
• Maintained maven integration to ensure all of the unit tests were running properly
• Followed the scrum methodology with weekly sprints
• Wrote unit tests in JUnit and JMock to ensure proper test coverage
• Performed some regression tests to ensure each part of the software was up to standard
• Technologies used: Java/J2EE, Ant, Maven, SQL, JSP, CSS, JavaScript, Hibernate, HQL, jBoss, Spring, Eclipse, Jira, Hudson, Jenkins, Subversion, Scrum, JUnit, JMock, PostgreSQL, MySQL, OpenLDAP.

Sep 2011 – Dec 2011 · 3 mos

• Debugged various problems using WireShark to perform packet analysis on various message types including SIP Messages and TCP/IP Messages
• Worked in JUnit and SIP Unit to automate Instant Messaging and SIP VoIP calls
• Performed regular sanity testing and regression testing to ensure various features in IMS, Standalone, and SSL infrastructures were up to standard
• Mentored a new full-time employee and familiarized them with the environment
• Technologies Used: Java, SIP, TCP/IP, RTP, TLS, UDP, WireShark, Red Hat variant of Linux, JUnit, 3GPP IMS Server Configuration(I, P, S-CSCF, HSS, A2 Server), SSL Infrastructure, SIP Unit.

Jan 2011 – Apr 2011 · 3 mos

• Developed in Java to add features and fix defects to their primary product
• Worked in a Client-Server architecture; implemented changes both server side and client side
• Maintained the Hudson/Jenkins build server by ensuring that the ANT build scripts were functional
• Managed the Scrum team’s weekly point capacity (weekly team quota)
• Technologies Used: Java, Oracle, Ant, Hudson/Jenkins, Guice, Jira, HP Quality Centre, BugZilla, EasyMock, PowerMock, JUnit.