Respectful self-motivator gifted at finding reliable solutions for software issues. Looking forward for challenges and to solve them with Analytical approach with result oriented output
Designed backend services for edge devices (Jetson TX2, Raspberry Pi) to store and sync AI-detected vehicle data.
Built REST APIs and dashboards using Django, DRF, and PostgreSQL for multi-location access monitoring and analytics.
Developed “Connect” – a cloud-based portal aggregating data from all edge devices for real-time insights.
Implemented TAT (Turnaround Time) alerts and vehicle intelligence features (brand, color, model detection).
Automated reports and alerts using Playwright, OpenPyXL, and email systems.
Optimized log storage using pg_partman and pg_cron with time-based PostgreSQL partitioning.
Integrated UPI (PhonePe) payments and dynamic parking pricing for 2W/4W vehicles.
Built async workflows with Celery, RabbitMQ, Redis, and APScheduler.
Reduced Docker image size by 50%+ for Python (using python-slim + multi-stage) and React (converted to Nginx static container).
Centralized routing and HTTPS handling with Nginx Proxy Manager, enabling future scalability and caching.
Implemented vector-based search using Milvus and LLM-generated embeddings for highway products.
Enabled semantic search of past incidents from vehicle images by converting natural language queries to vector format.
Deployed and managed infrastructure on Oracle Cloud Infrastructure (OCI) – VM instances, Object Storage, etc.
FastAPI Udemy
FastAPI Udemy
IBM Advance Data Science Coursera