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Computer Vision Engineer

Kanz
Riyadh, KSA
fulltime
Entry
1 weeks ago
computer visiondeep learningCNNimage processingOpenCVPyTorch
Free

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computer visiondeep learningCNN
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Overview

Jobs for Humanity is partnering with kanz to build an inclusive and just employment ecosystem.

Therefore, we prioritize individuals coming from all walks of life.

Company Name: kanz

We are seeking a talented and driven Computer Vision Engineer to join our dynamic team.

In this role, you will be at the forefront of building intelligent visual perception systems that power real-world applications.

You will work on cutting-edge challenges involving object detection, image segmentation, and video analysis, transforming complex research into scalable, production-ready solutions.

If you are passionate about pushing the boundaries of what machines can see and understand, this is the opportunity for you.

Job Purpose

The primary purpose of this role is to design, develop, and deploy robust computer vision algorithms and deep learning models that solve real-world problems.

You will be responsible for the entire lifecycle of model development—from prototyping and training to optimization and deployment on edge devices or cloud platforms—ensuring high performance, accuracy, and reliability in production environments.

Job Duties And Responsibilities

  • Design, develop, and deploy computer vision algorithms and models for real-world applications such as object detection, image segmentation, or video analysis.
  • Demonstrate proficiency in Python and deep learning frameworks including PyTorch or TensorFlow.
  • Apply experience with image processing libraries such as OpenCV for visual data manipulation.
  • Optimize computer vision models for deployment on edge devices or cloud platforms.
  • Manage data pipelines and conduct model evaluation to ensure robust performance in production environments.

Required Qualifications

  • Computer Vision
  • Python
  • PyTorch
  • TensorFlow
  • OpenCV
  • Model Optimization
  • Edge Deployment
  • Cloud Deployment

• Data Pipeline Management

  • Model Evaluation

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