Computer Vision Engineer 1-3 yrs

Key Responsibilities

● Design, develop, and implement perception algorithms for various

applications, including object detection, tracking, classification, and scene

understanding.

● Work extensively with video and image processing techniques, including:

● Image Processing: Noise reduction, feature extraction, image

segmentation, image enhancement, color space manipulation,

geometric transformations.

● Video Stabilization: Real-time video stabilization techniques for noisy

or shaky camera inputs.

● Motion Estimation: Developing techniques to estimate the motion of

objects or the camera.

● Develop and integrate perception pipelines using NVIDIA DeepStream and

GStreamer for high-performance, real-time processing.

● Optimize perception algorithms for deployment on edge computing platforms

such as Jetson, considering constraints such as power, memory, and

computational resources.

● Collaborate closely with hardware engineers, and software engineers to

integrate perception solutions into larger systems.

● Stay up-to-date with the latest advancements in computer vision, deep

learning, and robotics perception.

Skills and Requirements

● Bachelor's degree in Computer Science, Electrical Engineering, Robotics, or a

related field.

● Approximately 1-2.5 years of professional experience in Computer Vision

domain.

● Strong proficiency in C++ and Python.

● Hands-on experience with NVIDIA DeepStream SDK for building real time

streaming applications.

● Demonstrable experience with GStreamer for multimedia pipeline

development.

● Extensive experience with image processing techniques (e.g., OpenCV).

● Strong understanding and practical application of video stabilization

algorithms.

● Experience with object detection, tracking, and classification.

● Familiarity with various computer vision algorithms and their applications.

● Experience in solving AI-related problems, particularly in the context of

computer vision and real-time inference.

● Practical experience in optimizing and deploying models on edge computing

devices.