Murali Marupudi

About

Backend engineer focused on high-throughput Python/Flask systems on AWS, with strong scaling and performance tuning experience (e.g., PostgreSQL join reduced from ~3s to <200ms; background aggregation cut from 10 minutes to <90 seconds with 8x throughput). Has also integrated ML model serving into production APIs (churn prediction) using Celery/Redis batching and AWS Lambda/S3, and designed secure multi-tenant architectures with PostgreSQL schema isolation and row-level security.

Experience

Education

Key Strengths

• Designed and built scalable Flask microservices with layered architecture
• Scaled high-traffic services using Celery + Redis, Gunicorn workers, and AWS load balancing
• PostgreSQL/SQLAlchemy performance optimization (composite index reduced join from ~3s to <200ms)
• Integrated ML workflows into backend systems (Flask model-serving APIs with AWS Lambda/S3 pipelines)
• Reduced ML inference latency via batching + async processing + Redis caching (70% response-time improvement)
• Implemented secure multi-tenant data isolation (schema-based isolation + row-level security + tenant-context validation)
• Improved background processing throughput by offloading aggregation to Celery and caching (10 min to <90 sec; 8x throughput)
• Improved backend efficiency by ~25% using JavaScript and SQL optimizations
• Increased user engagement by ~30% via responsive front-end improvements (HTML/Bootstrap)
• Rewrote core functions in a data visualization JS library using ES6 (Map/Set) for performance
• Implemented lazy loading to reduce memory footprint and improve rendering time by ~40%
• Resolved async rendering delays by optimizing state management and adding throttling
• Diagnosed performance issues using logs and backend metrics to pinpoint bottlenecks
• Optimized database performance via indexing, join refinement, and caching for high-traffic paths
• Maintains developer communication through detailed release notes and proactive user outreach
• Keeps documentation current by linking doc tasks to Jira tickets and reviewing during sprint milestones