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TAYEE.AI · Careers
Autonomous Vehicle Software Systems Engineer
Build the bridge between on-vehicle autonomous driving software, the cloud, in-vehicle hardware and the driver — ensuring high reliability, fail-safety and a great HMI experience.
Responsibilities
- Vehicle-cloud communication architecture: develop and maintain high-performance protocols (MQTT, SOME/IP, DDS or custom TCP/UDP); handle real-time status reporting and reliable reception of cloud commands (OTA, remote takeover, path planning); optimize links with caching and retransmission under weak networks
- Vehicle health management and fault diagnosis: build the fault library with severity levels; develop self-check programs monitoring sensors (LiDAR, cameras, IMU), compute units and actuators; design fault isolation mechanisms
- Functional safety and emergency strategies: develop emergency handling modules triggering minimal-risk maneuvers by fault level; implement degradation logic; build watchdog programs for auto-recovery or safe stop
- HMI backend and voice broadcast integration: implement voice broadcast logic converting system status, fault alerts and navigation into voice output; define vehicle status display interfaces with the HMI frontend team
- System integration and performance optimization: port and adapt system software across hardware platforms (IPC, Orin, etc.); analyze CPU/memory/network usage and optimize for real-time performance
Requirements
- BSc or above in Computer Science, Automation, Vehicle Engineering or related; proficient in C/C++ with Linux or QNX development experience; deep understanding of multi-threading, multi-process programming and IPC (shared memory, DDS, Socket)
- Familiar with vehicle-cloud protocols (MQTT, HTTP/2, gRPC) and in-vehicle protocols (SOME/IP, DDS, CAN); ROS/ROS2 or CyberRT experience is a plus
- Strong Linux system knowledge and system-level debugging; understanding of functional safety concepts; fault diagnosis and health management software experience preferred
- Holistic understanding of autonomous driving architecture (sensors, perception, localization, planning, control data flow); TTS or in-vehicle HMI experience is a plus
- Strong sense of responsibility and reverence for autonomous driving safety; strong logical troubleshooting ability
- Plus: automotive-grade project delivery experience; Docker containerization on vehicle platforms; on-road test and debugging experience