Summary
Naren Dhyani is a software engineer at Amazon with 8 years of experience building and scaling machine learning systems that bridge research and production. He has a strong research pedigree from NYU where he developed SOTA techniques to reduce Vision Transformer inference latency, and has translated that work into production-ready solutions across startups and enterprise environments. Skilled in PyTorch, JAX, TensorFlow, CUDA, Java, TypeScript, and AWS, he pairs model optimization know-how with solid engineering practices and big-data experience (Hadoop/Hive). Naren is especially interested in hardware-software co-design—exploring compilers and ML accelerators to squeeze more performance from models—and has a track record of deploying compressed models to resource-constrained devices. Based in Seattle, he combines academic publication experience with pragmatic product impact, making him adept at turning cutting-edge research into scalable infrastructure.
8 years of coding experience
5 years of employment as a software developer
Indian Institute of Technology Bombay
Master of Science - MS, Computer Engineering, Master of Science - MS, Computer Engineering at New York University
Hindi, English