Job Description
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company.” We're looking to grow our company, and build our teams with the smartest people in the world. Join us at the forefront of technological advancement!
We are currently seeking a software engineer intern with strong Computer Vision and Deep Learning fundamentals and robust C++ skills to contribute to the development of RTX Broadcast engine - a comprehensive suite of SDKs and libraries that enable AI-driven broadcast features.
You will work alongside brilliant engineers on core technologies, and implement and optimize software to solve challenging computer vision and deep learning problems related to image and video processing. You will have the opportunity to innovate on algorithms , optimize for RTX Tensor cores and present or demo your state -of-the-art work across the company. You will work collaboratively with research and production teams on new groundbreaking approaches that transform the gaming industry.
You will gain first-hand experience and grow your technical expertise in one or multiple areas of:
- Face detection, tracking and expression estimation.
- Background segmentation
- Body motion capture and estimation
- Hand pose prediction and recognition
- Video artifact removal and super resolution
- Video style transfer
- 3D reconstruction and scene understanding
Qualifications
- Pursuing BS, MS, or PhD in Computer Science or related field
- Hands on experience with building, training and debugging neural networks
- Hands on expertise with one or more Deep Learning frameworks (Caffe, tensorflow, keras etc)
- Strong software engineering background, Proficiency in C++ programming.
- Self-motivated, fast to act and eager to learn as well as guide design
- Experience of using deep learning in computer vision
- Experience with CUDA programming, and a real passion for optimizing system performance.
- Experience with SDK development