# Howard Nguyen > AI/ML Serving @ Pinterest Location: United States, United States Profile: https://flows.cv/howardnguyen Senior software engineer with 10+ years of experience scaling high performance distributed systems and AI/ML infrastructure ## Work Experience ### Senior Software Engineer (AI/ML Serving) @ Pinterest Jan 2021 – Present | San Francisco Bay Area ### Senior Software Engineer (ML Platform) @ Facebook Jan 2018 – Jan 2021 | Greater New York City Area Senior software engineer at Instagram Machine Learning (IGML), a platform responsible for sourcing and recommending all Instagram related content • Led a project to track and manage demand within IGML. This included implementing distributed tracing for client cost attribution, aggregating metrics across shared services, and creating a standard system for regression detection and admission control. Also delivered team wide keynote and workshops on managing resources solving future regressions, and best practices • Led efforts to map the data lineage of IGML’s ecosystem into a knowledge graph then delivered a stakeholder keynote on how to leverage it for better dependency management, privacy control, and cost benefit analysis • Led a project to restrict access and enforce deletion of personally identifiable information • Rearchitected IGML client logging and realtime processing services into a more efficient layer that reduced host footprint by 25% • Cut realtime feature storage footprint by 20% by deleting features with low model significance • Optimized feature storage serialization and batched key records based on access pattern to reduce footprint by 30% and cache latency by 15% • Migrated ML features to new framework which allowed the deprecation of a legacy feature framework- saving 75% of database write QPS, 10% of fleet size, and increased engagement by 0.7% ### Lead Back End Developer @ Modsy Jan 2017 – Jan 2018 | San Francisco Bay Area Modsy allows you to visualize your designs and furniture in your home before you buy it using realistic 3D renderings. • Built and scaled a custom, in-house 3D render job pipeline • Saved customer success 20 hours/week by creating an order management system with automated product refunding • Improved query times by 50% and unified data access patterns by creating a data access layer for products and 3D render jobs • Refactored and removed 20,000 lines of code within the first 3 months • Increased unit test coverage from 58% to 80% by standardizing good coding practices and review • Improved site reliability after benchmarking and refactoring expensive APIs and queries • Created a release tool to automate deploys and release note creation that decreased deploy time by 5 hours/week • Created an asynchronous job to parse and convert 3D asset files into V-Ray renderable files • Provided real-time support for critical bugs using Bugsnag, Papertrail, Fullstory, and CloudWatch ### Software Engineer @ Captricity Jan 2015 – Jan 2017 | Oakland, CA Captricity is a management platform that captures and converts data generated by paper forms into business-ready information with an industry leading accuracy rate of 99.9%+. • Increased workforce throughput by using Celery to asynchronously batch Amazon Human Intelligence Tasks (HITs) based on perceived effort, task type, and completion time • Decreased job latency by building near real-time repricing of undesirable Amazon Human Intelligence Tasks (HITs) • Designed and created a new regex model to support forms with pages that are optional, repeating, and out of order • Increased system reliability by helping migrate a part of job pipeline into a separate microservice • Decreased system downtime through throttling and splitting of large jobs that consumed excessive resources • Improved customer turnaround time using job prioritization based on service level agreement (SLA) • Ensured system scalability via benchmarking, optimizing Postgresql queries, and segregating Celery infrastructure • Provided real time support during system outages using Airbrake, Splunk, NewRelic, and custom monitoring integrations • Mentored two summer full-stack interns and helped them deliver core improvements on form setup and configuration ### Software Engineer Intern @ Natero Jan 2014 – Jan 2014 | Palo Alto, CA Natero is a customer success platform that uses machine learning to predict user behavior and big data analytics for deep customer insight. • Built a JSON configuration compiler to chain Hadoop MapReduce jobs and perform cohort analysis on large datasets • Implemented client retention rate and "layer cake" plot visualizations using d3 • Created a custom LRU Redis cache with locking for parallel operations and manual garbage collection ### CS61A Academic Intern @ UC Berkeley Jan 2013 – Jan 2013 | Berkeley, CA Assisted in teaching CS 61A by holding office hours, answering questions on Piazza student forum, leading section warm-ups, and helping TAs lab. ### Hardware and Software Intern @ Flowbit, Inc. Jan 2013 – Jan 2013 | Berkeley, CA Flowbit is a remote water monitor for the developing world. It was featured in Bloomberg's first hackathon and was awarded first place in the University Mobile Challenge. * Designed and integrated the Arudino with GPS shield, GPRS shield, RTC, and flow meter * Programmed the Arduino to send SMS, receive GPS information, and process flow meter data * Optimized Arduino for power consumption ## Education ### Bachelor of Science (B.S.) in Electrical Engineering and Computer Science, Computer Science University of California, Berkeley Jan 2011 – Jan 2015 ## Contact & Social - LinkedIn: https://linkedin.com/in/howardanguyen - Website: http://howardanguyen.com/ --- Source: https://flows.cv/howardnguyen JSON Resume: https://flows.cv/howardnguyen/resume.json Last updated: 2026-03-22