Akshay Raghavendra Technology leader whose work has been judging which technical bets hold up and turning them into durable product decisions. Since January 2026, has independently framed and pressure-tested company-formation theses against technical feasibility, product leverage, and market structure, across world models and inference infrastructure for physical AI. Brings first-principles depth across an unusual range: wafer-scale AI at Cerebras; autonomous-vehicle perception, evaluation, and cloud security at NVIDIA; silicon-to-OS media architecture at Apple; and published ML research from a cancer drug discovery program. Has aligned research, compiler, platform, and product teams around architectural decisions at all three companies.
Deep Tech
Technology Leader — Video Systems
Deep Learning Architectures — NLP
Architect — Deep Learning, Security, Media Systems
Shaped architectural direction for NVIDIA DriveNet perception systems, aligning model behavior, evaluation, inference performance, and production constraints for autonomous-driving programs. Led training and evaluation of object-detection models including Mask R-CNN, YOLO, and SS
Software Development Engineer — Network Management Systems
Built reliability infra for scalable network services in C++/STL; ported async I/O, Windows to Unix.
Master of Science
Bachelor of Engineering
