Responsibilities
- Develop and maintain camera drivers and middleware for Nvidia Jetson platforms (TX2, Xavier, Orin), ensuring high-throughput, low-latency image acquisition.
- Integrate and optimize MIPI CSI camera interfaces, managing sensor communication, initialization, tuning, and Image Signal Processing (ISP) pipelines.
- Implement and optimize camera pipelines using Nvidia Argus APIs, leveraging both legacy and modern versions for sensor integration and processing.
- Enhance the image processing pipeline by utilizing hardware acceleration (CUDA, TensorRT, or Jetson ISP hardware) for real-time performance improvements.
- Develop real-time post-processing algorithms, handling sensor fusion, exposure correction, noise reduction, and multi-camera synchronization.
- Optimize memory and data handling strategies to process high-bandwidth video streams efficiently on embedded systems.
- Debug and optimize production-grade C++ firmware, applying multi-threading, system profiling, and performance tuning techniques.
- Work with edge AI processing, integrating perception models with GPU acceleration or specialized hardware for intelligent vision on-device.
- Collaborate with hardware engineers to bring up new imaging hardware, debug MIPI CSI interfaces, and fine-tune ISP configurations for various lighting conditions.
- Ensure reliability and robustness through rigorous testing, validation frameworks, and fail-safe mechanisms for camera firmware.
Qualifications
- Extensive experience in developing and shipping optimized, production-grade C++ software for embedded systems.
- Strong expertise in camera driver development and sensor integration on Nvidia Jetson platforms (TX2, Xavier, Orin).
- Hands-on experience with MIPI CSI camera interfaces, including low-level sensor initialization, ISP tuning, and frame processing.
- Deep knowledge of Nvidia Argus libraries, including both legacy and modern implementations, for camera sensor integration and processing.
- Understanding of image signal processing (ISP), exposure control, HDR imaging, sensor calibration, and tuning.
Preferred Qualifications
- Experience with Nvidia CUDA, TensorRT, or other hardware acceleration frameworks for high-performance vision processing.
- Familiarity with distributed systems or remote services, particularly in multi-sensor or networked robotic applications.
- Knowledge of optical systems and camera hardware, including lens distortion correction, image tuning, and calibration.
- Experience integrating camera systems into SLAM, multi-sensor fusion, or AI-based perception pipelines.

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