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.
As a Vehicle Systems Engineer, you will be responsible for the development, integration and testing of software and libraries of various systems on autonomous vehicle test vehicles. You will work cross-functionally with trajectory and planning algorithm engineers, perception and localization engineers and cloud robotics developers. The role also includes system and module level tests in the field and rapid response to issues as they arise.
- Building/Integrating software: develop, modify, test and debug autonomous driving software during vehicle field tests
- Write unit tests and documentation.
- Write efficient networking code between the various vehicle level autonomy software and other on-board APIs.
- Integrate HW and SW systems on the vehicle for new or modified vehicle functionality, enhance performance by cross-functionally coordinating and implementing SW fixes/enhancements with autonomy team
- Develop scripts to improve workflow and test task execution
- All other duties as assigned
- B.S in CS/EE or other related field.
- Experience with ROS middleware or other such frameworks
- Extensive software development experience (C/C++, Python)
- Experience with Linux (networking, performance monitoring)
- Extensive experience with programming and software integration
- 2+ years experience in Linux kernel and/or robotics middleware frameworks
- Experience in device driver designs that involve sensor control and data acquisition.
- Experience with message protocols (protobuf, CAN)
- Vehicle integration experience including hands-on bring-up and testing of compute, sensors, power distribution systems
- Experience with a real-time control system or embedded OS.
- Experience with x86 and ARM based architecture.
- Experience with Nvidia GPUs libraries/SDKs, Open CV, Tensorflow
- Extensive experience with autonomous vehicle sensors – IMU/GPS, lidars, machine vision cameras, ultra-sonics, radars etc.