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 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