Summary
Nived Narayanan is a software engineer specializing in deep learning frameworks and compiler-front-end optimizations, with a decade-long professional horizon and 2+ years focused on DL system performance for edge AI hardware. He has driven tangible gains—optimizing YOLOv3, ResNet50 and MobileNetv2 for 2K–8K inputs on constrained 3MB, 4 TOPS hardware, refactoring a memory execution planner for a 40% runtime improvement, and automating verification flows to boost workflow efficiency by 70%. At Roviero he bridged software and silicon, implementing layer-level memory optimizations in close collaboration with hardware teams and now maintains a custom DL framework and RAM utilization strategies for AI chips. Curious and self-driven, he blends systems engineering rigor with rapid automation to make complex models run reliably on resource-constrained devices.
10 years of coding experience
3 years of employment as a software developer
Bachelor of Technology - BTech, Computer Science, Bachelor of Technology - BTech, Computer Science at Vidya Academy of Science and Technology