Must Have
1+ years of qualified experience in C++ and Python.
Solid 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 skilled experience in the Computer Vision domain.
Solid 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.
Valuable 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.

📌 Perception Engineer Bengaluru
🏢 Paarvision Autonomy
📍 Bengaluru