Perception Software Engineer - Autonomous Vehicles


South Korea, remote

full time

22 Jan 2021


Intelligent machines powered by Artificial Intelligence computers that can learn, reason and interact with people are no longer science fiction. GPU Deep Learning has provided the foundation for machines to learn, perceive, reason and solve 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 an extraordinary Autonomous Vehicle Perception SW Engineer to develop and productize NVIDIA's autonomous driving solutions.

As a member of our perception team, you will work on building world-class obstacle perception SW utilizing multiple sensor modalities (e.g., camera and radar). You will be challenged to improve robustness and computational efficiency of obstacle perception algorithms under challenging and diverse scenarios to fully enable autonomous driving anywhere and anytime. You will also contribute to algorithm aspects of obstacle perception such as state estimation/multi sensor fusion.

What you'll be doing:

  • Develop highly efficient product code in C++ for obstacle perception algorithms using multiple sensor modalities.
  • Research and develop state-of-the art state estimation/sensor fusion algorithms to improve obstacle perception output quality under diverse challenging scenarios.
  • Make sure our algorithms work well on real and synthetic data, in a diverse range of environments and conditions.

What we need to see:

  • MS or PhD in Computer Science or related fields and 2+ years of work experience.
  • Strong programming skills in C++ and python.
  • Hands-on experience in developing algorithms for state estimation/multi sensor fusion.
  • 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:

  • Hands-on experience and deep knowledge in CUDA programming.
  • Hands on experience in deploying SW to embedded platforms for real time applications.

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