Kiran M

About

Backend/ML integration engineer with experience at Accenture and Walmart building Flask-based analytics and prediction APIs on PostgreSQL/MySQL. Strong focus on performance and scalability—uses precomputed aggregates, Redis caching, query tuning (indexes/partitioning/EXPLAIN), and async/background processing; also designs secure multi-tenant isolation with JWT and schema/db-per-tenant strategies.

Experience

Education

Key Strengths

• Designed and built analytics/reporting APIs with Flask using layered architecture
• Performance optimization of heavy aggregation workloads via precomputed summary tables and caching (seconds to milliseconds)
• Database performance/scalability tuning with SQLAlchemy + PostgreSQL (indexes, partitioning, query profiling with EXPLAIN ANALYZE)
• Productionizing ML models as API services (model packaging/serialization, consistent feature engineering between training and inference)
• Scalability patterns for ML APIs: load model at startup, stateless services, horizontal scaling (containers/AWS Lambda), queue + batch processing for spikes
• Multi-tenant data isolation using tenant_id filtering plus stronger isolation via schema/db-per-tenant and JWT-based enforcement
• Improved high-traffic e-commerce performance by moving synchronous work to background workers and adding Redis caching to reduce DB load and prevent peak-time timeouts
• End-to-end full stack delivery (backend, frontend, cloud deployment, CI/CD)
• Designed and built Java Spring Boot microservices for inventory, orders, and financial transactions
• Improved transaction throughput by ~22% through performance optimization
• Built responsive React.js UI for an e-commerce platform
• Implemented robust REST API practices (error handling, validation, logging)