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Mid-Level Computer Vision Engineer

Function: Technology
Location: Remote
Job Type: Permanent/Full time

May 03, 2024

Company Overview:

Uqudo is a leading digital identity and eKYC company revolutionising the way organisations verify identities and comply with KYC, AML, and CDD regulations. Utilising advanced digital identity technology powered by AI, cognitive document analysis, and facial recognition, Uqudo offers a secure, seamless onboarding experience while mitigating fraudulent activities. Our award-winning tech platform drives digital transformation globally, earning accolades across the Middle East and Africa and forming partnerships with industry leaders such as VISA, SmartAfrica, and Microsoft. As part of our innovative team, you’ll contribute to projects at the forefront of identity verification and digital transformation.

Job Description:

We are seeking a talented Mid-Level Computer Vision Engineer to join our AI team at Uqudo. In this role, you will work on cutting-edge projects related to document analysis and KYC, leveraging powerful AI technologies to drive innovation in digital identity verification.

Key Responsibilities:

  • Design, develop, and deploy computer vision algorithms and AI models for various applications including image classification, image segmentation, object detection, text detection and recognition, and document analysis.
  • Implement and optimise deep learning architectures using frameworks such as TensorFlow/Keras or PyTorch.
  • Collect, clean and label image datasets for various tasks.
  • Contribute to the development of new features and solutions to enhance our digital identity platform.
  • Maintain and improve our existing algorithms and models, including continuous evaluation, gap analysis, re-training, and fine tuning.
  • Collaborate with cross-functional teams to integrate computer vision solutions into larger systems.
  • Stay updated with the latest advancements in computer vision research and incorporate relevant techniques into projects.

Requirements:

  • Master or engineering degree in computer science or a related field.
  • Solid understanding of computer vision fundamentals, including traditional image processing techniques for feature extraction.
  • Previous hands-on experience training and fine-tuning deep learning models for computer vision tasks.
  • Strong proficiency in Python; knowledge of C/C++ is desired.
  • Experience with deep learning frameworks such as TensorFlow/Keras and PyTorch, as well as computer vision libraries like OpenCV and scikit-image.
  • Experience in using deep learning frameworks for mobile and / or IoT devices inference is a plus (e.g. TensorFlow lite).
  • Strong problem-solving skills and attention to detail, with the ability to work effectively in a collaborative team environment.

To apply, click here.