Perception Engineer

Job description Must Have

• 1+ years of professional experience in C++ and Python.
• Strong hands-on experience with OpenCV and implementation of image processing algorithms.
• Solid understanding of camera fundamentals, including camera calibration, intrinsic and extrinsic parameters, focal length, field of view (FOV), lens distortion, perspective projection, and image formation.
• Good familiarity with video streaming protocols, multimedia pipelines, and hardware/software encoders (RTSP, H264/H265, GStreamer, FFmpeg, etc.).

Key Responsibilities

• Design, develop, and implement multi-camera real-time streaming systems on edge devices, supporting features such as object detection, multi-object tracking, classification, and scene understanding.
• Develop, optimize, and integrate perception pipelines using NVIDIA DeepStream SDK and GStreamer for high-performance, low-latency video analytics.
• Optimize computer vision and AI workloads for deployment on NVIDIA Jetson and other edge computing platforms, considering power, memory, latency, and computational constraints.
• Integrate USB, CSI, and other cameras into production-grade applications.
• Collaborate closely with hardware, embedded, AI, and software engineering teams to deliver robust perception solutions.
• Debug and optimize camera interfaces, streaming pipelines, synchronization issues, and inference performance. Skills & Requirements
• Bachelor's degree in Computer Science, Electrical Engineering, Robotics, Electronics, or a related field.
• 1–3 years of professional experience in the Computer Vision domain.
• Strong programming skills in C++ and Python.
• Hands-on experience with NVIDIA DeepStream SDK for building real-time streaming and video analytics applications.
• Demonstrable experience with GStreamer for multimedia pipeline development and debugging.
• Extensive experience with OpenCV and classical image processing techniques.
• Experience implementing object detection, multi-object tracking, and image classification pipelines.
• Good understanding of camera vision fundamentals, and respective algorithms.
• Familiarity with computer vision algorithms and their practical applications in real-time systems. Bonus
• Experience with NVIDIA Jetson platforms (Nano, Xavier, Orin).
• Experience with ROS2
• Experience with CUDA, TensorRT, or ONNX model deployment.
• Familiarity with Docker and edge AI deployment.
• Experience optimizing real-time video processing pipelines for performance and low latency.