We're the driverless car company. Come work with a team of Computer Vision PhDs and MSs on technically challenging problems, building products that improve lives and prevent car accidents.
Our first product has been a Highway Autopilot that can be installed on almost any car. It uses an array of sensors and actuators to safely navigate along the highway. To use it, just drive into a lane on the highway and push a button.
Our team is small, but we move quickly. In less than a year, we've built prototype vehicles that have logged thousands of autonomous miles on California highways.
As a computer vision R&D engineer, you will work with the computer vision team to develop and implement effective and efficient algorithms for:
- Feature Detection
- Feature Tracking
- Lane Tracking
- Detection & recognition of dynamic and static objects
Dynamic objects include other cars on the road, motorcycles, bicyclists, pedestrians, and generic obstacles. Static objects include: road signs (exit signs, speed limits, etc.), construction zones/markers, road flares, medians, and curbs. Core technology development will center around improving the robustness of our vision systems to changes in lighting conditions or shadows, and training and evaluation various machine learning methods for use in object detection. You will also work closely with the localization and mapping team to integrate new image feature detectors for use in real-time localization.
Bonus points for experience with structure from motion (SfM), stereo vision processing and/or multi view reconstruction, OpenCV, ROS, CUDA.
Perks include working on challenging problems that have real-world applications, a competitive salary & equity, and of course, rides in self-driving cars!