Perception Engineer

Reposted One Month Ago
Bengaluru, Bengaluru Urban, Karnataka, IND
In-Office
Junior
Artificial Intelligence • Computer Vision • Robotics • Defense
The Role
Design and implement real-time multi-camera perception pipelines on edge devices using C++/Python. Integrate USB/CSI cameras, build object detection, multi-object tracking, classification, and scene understanding. Optimize and deploy high-performance, low-latency video analytics with NVIDIA DeepStream, GStreamer, and Jetson platforms, and debug streaming, synchronization, and inference performance.
Summary Generated by Built In

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.

Skills Required

  • 1+ years professional experience in C++ and Python.
  • Strong hands-on experience with OpenCV and image processing algorithms.
  • Good familiarity with video streaming protocols and multimedia pipelines (RTSP, H264/H265, GStreamer, FFmpeg).
  • Solid understanding of camera fundamentals (calibration, intrinsic/extrinsic parameters, focal length, FOV, lens distortion, perspective projection, image formation).
  • 1-3 years of professional experience in the Computer Vision domain.
  • Hands-on experience with NVIDIA DeepStream SDK for real-time streaming and video analytics.
  • Demonstrable experience implementing object detection, multi-object tracking, and image classification pipelines.
  • Experience integrating USB, CSI, and other cameras into production-grade applications.
  • Bachelor's degree in Computer Science, Electrical Engineering, Robotics, Electronics, or related field.
  • Experience optimizing computer vision and AI workloads for NVIDIA Jetson and other edge computing platforms (power, memory, latency constraints).
  • Experience with GStreamer for multimedia pipeline development and debugging.
  • 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.
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The Company
11 Employees
Year Founded: 2024

What We Do

Paar Autonomy is a deep-tech robotics startup specializing in autonomy solutions and AI-based vision systems for unmanned aerial, ground, and sea vehicles. The company develops multi-sensor, gyro-stabilized gimbal cameras and proprietary agentic AI models designed to provide 'super-human' vision and real-time mission coordination, primarily targeting the global defense market and dual-use industrial applications.

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