{"$schema":"https://raw.githubusercontent.com/jsonresume/resume-schema/v1.0.0/schema.json","basics":{"name":"Sahaj Chhabra","label":"Software Engineer","image":"https://saywise-production-profilepicturestoragebucket-kbfooccc.s3.amazonaws.com/profile-pictures/91cab858-f84e-49f5-b361-5d58e31d6743/linkedin-1791240550321.jpg","summary":"Full-stack engineer building AI-powered video and media systems at scale, from thumbnail generation pipelines to verticalization APIs and distributed encoding infrastructure.","location":{"city":"Canada"},"profiles":[{"network":"LinkedIn","username":"sahaj0312","url":"https://linkedin.com/in/sahaj0312"},{"network":"GitHub","username":"Sahaj0312","url":"https://github.com/Sahaj0312"}]},"meta":{"canonical":"https://saywise.com/member6268","version":"v1.0.0","lastModified":"2026-10-05T22:49:49.013Z"},"x_saywise":{"handle":"member6268","pronouns":null,"availability":null,"oneLiner":"Full-stack engineer building AI-powered video and media systems at scale, from thumbnail generation pipelines to verticalization APIs and distributed encoding infrastructure.","profileUrl":"https://saywise.com/member6268","markdownUrl":"https://saywise.com/member6268/profile.md","pdfUrl":"https://saywise.com/member6268/resume.pdf","archetype":{"code":"HS-MG","name":"Launchpad Trailblazer","url":"https://saywise.com/sca/620170636371","rarity":"One of the first Launchpad Trailblazers on Saywise"}},"work":[{"name":"Quickplay","position":"Software Engineer","location":"Toronto, Ontario, Canada","url":"https://quickplay.com","startDate":"2025-01-01","endDate":"2026-09-01","summary":"Built an end-to-end AI thumbnail generation pipeline combining computer vision for frame extraction with LLM-powered captioning for thousands of video assets. Designed and shipped a Verticalization API using YOLO object tracking to convert 16:9 videos to 9:16 vertical shorts at scale for the Pilipinas Live app. Engineered a Golang microservice to automate n8n workflow deployments, eliminating 90% of manual migration work. Architected a distributed HLS encoding system in Go generating adaptive bitrate streams for 20,000+ video assets using multithreading and Pub/Sub messaging."},{"name":"Instagrad","position":"Co-Founder & CTO","location":"Vancouver, BC","startDate":"2024-09-01","endDate":"2025-12-01","summary":"Co-founded an AI startup to streamline photo studio operations and secured a partnership with Vancouver's largest studio, gaining access to 10+ petabytes of image data to train a proprietary on-premise model for AI-generated graduation composites. Built an automated face-matching pipeline that ingests thousands of graduation photos and clusters them into per-student folders using facial recognition, replacing a manual sorting process."},{"name":"Quickplay","position":"Software Engineer Intern","location":"Toronto, Ontario, Canada","url":"https://quickplay.com","startDate":"2024-06-01","endDate":"2024-08-01","summary":"Implemented a GraphQL-to-SQL translation engine with nested query support and batch resolution to eliminate N+1 query overhead. Led testing efforts across multiple microservices with unit and integration tests in Go using table-driven patterns, increasing SonarQube test coverage from 14% to 97%. Collaborated with three cross-functional teams to build an internal tool converting legacy XML metadata files to JSON compatible with any web-based CMS."},{"name":"BMO","position":"Software Developer Intern","location":"Toronto, Ontario, Canada","url":"https://bmo.com","startDate":"2022-05-01","endDate":"2022-08-01"}],"education":[{"institution":"The University of British Columbia","studyType":"Bachelor's degree in BUCS","startDate":"2019-09-01","endDate":"2024-06-01"},{"institution":"GEMS Education","studyType":"International Baccalaureate","startDate":"2005-01-01","endDate":"2019-01-01"}],"projects":[{"name":"Pixitt","description":"Built a camera roll cleaning app using SwiftUI with a Tinder-like interface for deleting duplicate or low-quality photos. Implemented duplicate detection using perceptual hashing and on-device ML with MVVM architecture, asynchronous media loading, and optimized memory management to handle large photo libraries efficiently."},{"name":"InvestorAI","description":"Built a personal finance tool that uses LLMs to analyze stock portfolios and generate insights based on financial documents and market data. Created embedding pipelines using pgvector for context-aware retrieval with RAG architecture, deployed to Azure Kubernetes Service."},{"name":"Fit@Home","description":"Built an AI personal trainer for nwHacks that streams video over WebRTC to a Python backend using MediaPipe to track 33 body landmarks and calculate joint angles for real-time exercise form validation."}],"skills":[{"name":"Python (Programming Language)"},{"name":"JavaScript"},{"name":"MySQL"},{"name":"Java"},{"name":"HTML"},{"name":"Cascading Style Sheets (CSS)"},{"name":"Go"},{"name":"Swift"},{"name":"FastAPI"},{"name":"Flask"},{"name":"React"},{"name":"SwiftUI"},{"name":"LangChain"},{"name":"OpenCV"},{"name":"MediaPipe"},{"name":"Docker"},{"name":"Kubernetes"},{"name":"GCP"},{"name":"AWS"},{"name":"Azure"},{"name":"Git"},{"name":"PostgreSQL"},{"name":"n8n"},{"name":"LLMs"},{"name":"RAG"},{"name":"YOLO"},{"name":"Computer Vision"},{"name":"pgvector"}],"certificates":[{"name":"AI Fundamentals Certificate","date":"2026-09-01","issuer":"UnlockAI: Learn AI Daily"}]}