NVIDIA’s robotics platform ISAAC is a fast progressing effort inside the company and will have a decisive impact on the future progress of the robotics industry. We need passionate, hard-working and creative people to help us tackle more of the unique opportunities in the fast pace environment of modern robotics.

In our team, you will have the chance to work on the most advanced chips for robotics with standard robotics platforms. Solve the spatial reconstruction problem based on camera, Lidar, etc. You will be able to contribute to the next exciting industry in the world.

We are looking for software engineers to optimize our algorithm performance based on the most recent industry technology (including NeRF, feature map, etc) with our standard ISAAC platform. Your work on a very sophisticated problem will help to make the world better.

What You'll Be Doing:

• Work on the camera based SLAM system for both mapping and localization requirements

• Follow up with the industry leading localization algorithms on the ISAAC robotics platform

• Build a stable localization module, and show the customer our ability on robotics software and hardware

• Camera based dense spatial reconstruct along with the SLAM result

What we need to see:

• Bachelor, Master or PhD degree in computer science, computer engineering or equivalent experience with 5+ years of experience

• Compute vision related experience, especially with camera based mapping, NeRF and other state of art technology

• Experience with autonomous vehicles or mobile robotics

• A deep knowledge of software development skills (C++, Python).

• Strong design, coding and debugging skills.

• Strong communication and teamwork skills, as we work as a tightly knit team, always discussing and learning from each other.

• Highly motivated, hardworking and curious about new technologies.

Ways to stand out from the crowd:

• We would love to see a record of working and shipped solutions on related products.

• Background in experience of working with LiDAR/Radar/camera/IMU, etc

• Background in well-rounded knowledge of how an autonomous vehicle stack (or similar large system) works, and practical experience taking care of the challenges in integrating many components into one solution