At Udelv we are creating a new type of driverless vehicle. In January 2018 Udelv successfully accomplished the first ever autonomous commercial “last mile” delivery made on public streets using advanced transportation and autonomous driving technologies to revolutionize this segment of transportation. Since our launch we have been scaling rapidly to meet client demand in several states. Our engineers are working with real world scenarios and solving real issues to achieve true last mile autonomy.
Udelv's autonomous driving team is searching for an experienced artificial intelligence expert to lead the development of detection and segmentation tools that will extract environment information from LiDAR and camera sensor data streams. This expert will support the deployment and analysis of existing detection tools in an open-source autonomy stack, and will frame, implement, and train new tools that support the autonomy stack's perception requirements. They will collaborate with the company's broader autonomy engineering team.
- 4+ years of post-degree work with neural networks
- 3+ years selecting network architectures that balance efficiency and accuracy
- 3+ years training and deploying class-based detection neural nets
- 3+ years training and deploying image segmentation neural nets
- Experience working in a broader autonomous vehicle or robotics engineering team
- Track record of collaborative, team-based approach to software development
- C++ competency
- Deployment of neural nets on LiDAR point cloud, or other non-image, data
- Training and deploying lane- and free-space detection neural nets
- Working directly with autonomous driving software stacks
- Developing software in ROS, Cyber, or a similar robot operating system
- Python competency
- Masters or PhD degree in a computational, engineering, or math discipline