Description: Autonomous Driving R&D Engineer: Perception
We are growing our team working on solutions for future automated and autonomous vehicles in Palo Alto, CA and are looking for excellent candidates with expertise in perception system, object tracking, probabilistic grid representations, object tracking and data association for a position in the automated driving team.
Your Duties and Tasks:
Perform research and develop and implement algorithms in one or more of the following fields, applicable to automated vehicles:
- Sensor modeling and 3D point cloud fusion
- Probabilistic environment representation
- Object tracking and data association
- Computer vision (including object detection and classification)
Skills / Job Requirements:
- Ph.D. or M.S. in Computer Science, Engineering, or a related field
- Excellent knowledge and proven expertise in at least one of the fields: sensor fusion, probabilistic perception, object tracking, robotic computer vision.
- Excellent C++ programming expertise required, Python programming is a plus
- Proven system integration and software architecture skills
- Knowledge of Linux, and development on Linux systems preferred
- The ability to develop, understand and implement complex algorithms efficiently and correctly
- Experience with modern software engineering tools
- Experience working independently in a large software setting
- Experience working on robot and/or automotive electronics hardware a plus, as is experience with simulation environments and ROS
- Excellent communication skills and demonstrate a proven ability to multitask and deliver on challenging software development tasks
About Automated Driving at Bosch
Bosch has been working on autonomous/automated driving solutions in Palo Alto for many years. We have participated in the DARPA Urban Challenge as part of the Stanford Racing Team as well as Team AnnieWAY and we have collaborated with the Stanford Artificial Intelligence Lab's Autonomous Driving Team since 2007. We are now growing the team developing technologies for future autonomous vehicles (http://www.youtube.com/watch?v=0D0ZN2tPihQ).
For more information, and to apply online, please visit: http://bit.ly/1lYYx4N.