Intelligent machines powered by Artificial Intelligence computers that can learn, reason and get along with people are no longer science fiction. GPU Deep Learning has provided the foundation for machines to learn, perceive, reason and tackle problems. Now, NVIDIA’s GPU runs Deep Learning algorithms, simulating human intelligence, and acts as the brain of computers, robots and self-driving cars that can perceive and understand the world.
We are now looking for interns to develop and productize NVIDIA's autonomous driving solutions. As a member of our perception team, you will work on building world-class perception solutions based on multiple input modalities, such as cameras, radars, and ultrasonics. The primary approach will be deep learning. You will be challenged to improve robustness and accuracy as well as efficiency of the solutions to fully enable autonomous driving anywhere and anytime.
What You'll Be Doing:
Development: Perception development with application focus on highway driving, urban driving, and parking. Types of signals will include dynamic/static objects, traffic signs/lights, lanes, road markers, parking spots and nearby structures. Deep learning solutions and intelligent algorithm designs will be jointly used to develop the best in-class solutions.
Exploration: Research and develop innovative computer vision algorithms to improve output accuracy of various perception solutions under challenging and diverse scenarios.
Analysis and Experimentation: Identify and analyze the strength and weakness of the developed perception solutions using large scale data and improve them iteratively through meaningful metric building and optimization.
Productization: Productize the developed perception solutions by meeting product requirements for safety, latency, and SW robustness, especially for successful autonomous driving in Korea.
Data-driven Improvement: Drive and prioritize data-driven developments by working with large data collection and labeling teams to bring in high value data to improve perception system accuracy. Efforts will include prioritizing data collection, planning, and labeling to improve the value of data.
What We Need To See:
Pursuing BS/MS/PhD candidate in CS, EE, science or related majors
Hands-on work experience in developing deep learning and algorithms to solve complex real world problems, and proficiency in using deep learning frameworks (e.g., PyTorch).
Experience in data-driven development and collaboration with data and ground truth teams.
Strong programming skills in Python and/or C++.
Outstanding communication and teamwork skills as we work as a tightly-knit team, always discussing and learning from each other.
Ways To Stand Out From The Crowd:
Development Experience in autonomous vehicles : Shown expertise in developing perception solutions on diverse sensor modalities (e.g., cameras, ultrasonics, and radar).
Research Experience: Relevant publications related to perception tasks for autonomous driving, general computer vision and machine learning in leading conferences/journals.
Advanced Model Knowledge: Sophisticated visual recognition models, especially models for 2d/3d object detection, classification, license plate recognition and text recognition. Familiarity with bird's eye view perception solutions and techniques, and familiarity with common toolkits and libraries (e.g., MMDetection3D).
Ability to communicate in Korean and English fluently.
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