I design and build high-throughput, low-latency distributed systems, serverless data pipelines, and production ML integrations. My work focuses on scalable APIs, operational excellence, and data-driven systems for advertising and analytics.
Experience
Built high-scale distributed systems and AI-driven advertising infrastructure with focus on reliability, observability, and operational excellence. Designed scalable ad labeling services with multi-fold throughput improvements supporting sync/async workflows, and engineered serverless data lakes using DynamoDB, Apache Iceberg, AWS Glue, and Athena to achieve near real-time analytics SLAs.
Developed ultra-low-latency APIs with ElastiCache, GraphQL, and Step Functions processing thousands of TPS for real-time ad evaluation, pre-bid filtering, and publisher compliance. Optimized BrandSafety pipelines processing millions of products daily and led Ad Relevance API infrastructure that supported million+ TPS and multi-million dollar revenue impact.
Tech Stack: AWS (Lambda, EC2, Fargate, Batch Jobs, RDS, SNS, SQS, Step Functions, DynamoDB, Bedrock, Kendra, CloudWatch, Glue, Athena, ElastiCache, S3), Distributed Systems, Apache Iceberg, GraphQL, Kafka, Serverless Architecture, Machine Learning, CI/CD, Observability, Java, Python, TypeScript
Developed API integrations with Google Calendar and built ETL pipelines with data preprocessing for PostgreSQL database ingestion and optimization.
Tech Stack: Python, REST APIs, PostgreSQL, ETL Pipelines
Mentored students in Information Retrieval, Computer Security, Discrete Structures, and Numerical Computations courses. Researched fake news detection using machine learning and NLP at AI-SSGL lab. Developed automation scripts for grading and maintained research lab website.
Tech Stack: Python, Machine Learning, NLP, WordPress, Automation
Revamped ML test suites and built preprocessing tooling to accelerate NLP and unsupervised workflows, reducing runtime and manual effort. Created PyQt utilities for automated data preparation and visualization and prototyped ML solutions to improve software testing and evaluation.
Tech Stack: Python, Keras, PyQt, Machine Learning, NLP, Data Visualization, Test Automation
Education
Key Projects
Built a full-stack diabetes prediction app using a Random Forest model with Google Maps and Twilio for real-time alerts. Dockerized and deployed on AWS EC2 with PostgreSQL.
Developed an Android app (Java) for a football fantasy tournament and a Flask REST API + scraper to provide live data and scoring.
Architected a P2P distributed system with replication and version control to enable resilient file CRUD operations across nodes.
Technical Skills
Distributed systems design, high-throughput data pipelines, serverless architecture, API development and modeling, ML/AI integration, infrastructure and performance optimization, real-time event-driven systems, and observability.