Nvidia Internship

Nvidia WWFO Team is a dynamic group that is fast-paced and high-energy and I was fortunate enough to be a part of the team.

As a Deep Learning Engineer Intern, WWFO at NVIDIA, I was supposed to support the person in charge (PIC) -- tackling complex technical challenges and applications of modern deep learning techniques,

including: object detection, segmentation, video understanding, sequence prediction, language translation, text to speech and speech to text, adaptive computing, memory networks, reduced precision training and inference, graph compilers, reinforcement learning, search, distributed and federated training, and more.

Tasks and goals of the position:

1. Identifying the working of Ray-tune Hyper-parameter optimization (HPO) tools and Population Based Training (PBT) to perform efficient hyper parameter optimization search over a large space on various neural network architecture.

2. Getting familiarity with multitasking networks and to develop algorithms to make MT training highly efficient and deployable for real scenario usage like in autonomous vehicle.