AboutIndependent builder of production-grade systems: shipped an end-to-end URL shortener with JWT auth, Redis rate limiting/caching, Postgres, Docker, and real-time analytics, and separately architected a Redis-backed distributed task queue handling 1000+ tasks/min. Demonstrates strong distributed-systems instincts (atomicity, retries/DLQ, idempotency, heartbeats) plus a focus on maintainable code and self-documenting APIs (FastAPI/OpenAPI, versioned routes).
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Post a Role 90-day money-back guarantee Key StrengthsBuilt and deployed an end-to-end full-stack URL shortener (React/TypeScript + FastAPI) with JWT, Redis, PostgreSQL, Docker Performance under load: 500+ concurrent requests with sub-100ms response time Designed a distributed task queue processing 1000+ tasks/min with retries, DLQ, and idempotency Strong observability focus: real-time WebSocket dashboard for queue depth, worker status, throughput, and failures Debugged and fixed high-concurrency race conditions using Redis atomic operations and Lua scripting Improved production reliability with worker heartbeat monitoring and automatic restarts Maintainability practices: strict TypeScript, clean layering, reproducible dev env (Docker Compose), API documentation Shipped production RAG assistant with <2s end-to-end generation Reduced LLM JSON/structure failure rate from ~30% to <3% via chunking redesign + validation + retries Built multi-stage agent pipeline with typed contracts, schema validation gates, and request-context state tracking Strong LLM observability: stage-level metrics (latency, similarity scores, validation pass rate, retry rate) used to drive debugging/prioritization Designed offline/online/continuous evaluation loops; improved retrieval similarity (0.58→0.81) and validation pass rate (70%→97%+) Built robust data pipelines on messy ERP-like data with dbt tests, quarantine routing, and idempotent Airflow DAGs Prevented downstream analytics errors by adding temporal consistency validation for anomalous timestamps Like what you see? We'll introduce you to Vaishnavi directly.
Get Introduced ExperienceGraduate Research Assistant Georgia State University · Aug 2025 – Present part-time
Graduate Teaching and Lab Assistant Georgia State University · Aug 2024 – May 2025 part-time
Computer Vision & ML Engineer Atal Incubation Centre, AIC-GNITS Foundation · Jul 2023 – Jul 2024
AI/ML Research Associate Innovation and Incubation Cell - GNITS · Aug 2022 – Jun 2023
EducationGeorgia State University master, Computer Science (2026)
G. Narayanamma Institute of Technology & Science bachelor, Computer Science (2024)
Publications 2 publications
Machine Learning Computer Vision Healthcare Analytics
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