Developed high-performance system software in C/C++ and Python, optimizing memory management, process scheduling, and I/O operations.

Engineered multi-threaded and parallel computing solutions, reducing compute overhead and improving real-time processing.

Debugged low-level system issues, profiling CPU utilization, memory leaks, and kernel interactions using GDB, pdb, and dtrace.

Implemented load balancing and distributed caching strategies (Redis, Memcached, ccache, distcc), reducing latency and optimizing compute efficiency.

Architected containerized and virtualized environments with Docker, Kubernetes, and KVM, ensuring resource isolation and efficient orchestration.

Integrated monitoring and observability frameworks (Prometheus, Grafana, ELK Stack) for real-time system health tracking and anomaly detection.

Developed custom networking solutions, optimizing TCP/IP stack performance, packet processing, and secure communication.

Mentored 350+ students in DBMS, data structures, operating systems, and computer networks, assisting with error-debugging and coding in C/C++, Python, and JAVA.

Recommended cloud services based on use case needs, saving costs and improving efficiency.

Implemented test automation using Selenium and performed unit-testing on large server data.

Evaluated hardware capabilities and suggested efficient ways to connect smart meters, reducing costs by 15%.

Implemented a convolutional neural network-based vacant parking detector with OpenCV and YOLO modules.

Translated Python code to C++ to enhance the embedded system's runtime by 39%.