Posted:1 month ago|
Platform:
On-site
Full Time
for our platform. Your work will include integrating perception models, tuning planning algorithms,
optimizing performance on embedded hardware, and preparing the system for on-road deployment.
neural-network perception pipelines.
generators).
• Customize modules for hardware-specific constraints (sensors, compute platforms, CAN interfaces).
• Create tools for logging, visualization, and debugging of autonomous-driving behavior.
• Collaborate with mechanical, sensor, and platform teams to ensure robust integration on physical
vehicles.
• Contribute to safety, testing, and performance-validation frameworks.
• Experience with simulation tools (CARLA, Gazebo) and data-logging workflows.
• Strong debugging, optimization, and system-integration skills.
• Experience deploying on embedded compute (NVIDIA Jetson family).
• Background in ADAS or autonomous driving.
• Experience with CAN bus/vehicle interface integration.
• Knowledge of safety frameworks (ISO 26262, SOTIF).
• Understanding of reinforcement learning or end-to-end driving models.
The TFPL
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