# Algorithm Engineer( Computer vision) — AIQU

Canonical: https://jobxdubai.com/jobs/li-4471099637-algorithm-engineer-computer-vision
Location: Riyadh, Saudi Arabia
Type: full_time · Level: mid
Monthly salary: AED 17,640 to 29,400 per month (estimated, not employer-stated) (UAE salaries are tax-free)
Posted: 2026-09-27
Apply: https://www.linkedin.com/jobs/view/algorithm-engineer-computer-vision-at-aiqu-4471099637?_l=en

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## Description

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Responsibilities

• Develop and optimize computer vision algorithms, including object detection, image classification, and segmentation.

• Build and improve image/video datasets, including data cleaning, augmentation, annotation guidelines, and hard-case mining.

• Optimize models for different platforms through model compression, pruning, quantization, and inference acceleration using tools such as TensorRT, ONNX, and OpenVINO.

• Work with engineering teams to deploy CV models into production and address real-world and long-tail challenges.

• Keep up with the latest CV technologies and explore the application of Transformers and Vision Foundation Models.

Requirements

• Bachelor's degree or above in Computer Science, Software Engineering, Electronic Engineering, Automation, Mathematics, or a related field.

• Strong programming skills in Python and good knowledge of C/C++.

• Proficiency in at least one deep learning framework, preferably PyTorch; TensorFlow or JAX is also acceptable.

• Familiar with OpenCV, PIL, NumPy, and related tools.

• Solid understanding of CNNs and Transformers, such as ResNet, MobileNet, and ViT.

• Familiar with mainstream detection and segmentation models such as YOLO, RetinaNet, and Segment Anything (SAM).

• Strong analytical and problem-solving skills, with the ability to independently develop algorithm solutions for real-world business needs.

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## Requirements

Bachelor's degree or above in Computer Science, Software Engineering, Electronic Engineering, Automation, Mathematics, or a related field.
Strong programming skills in Python and good knowledge of C/C++. Proficiency in at least one deep learning framework, preferably PyTorch; TensorFlow or JAX is also acceptable.
Familiar with OpenCV, PIL, NumPy, and related tools.
Solid understanding of CNNs and Transformers, such as ResNet, MobileNet, and ViT.
Familiar with mainstream detection and segmentation models such as YOLO, RetinaNet, and Segment Anything (SAM).
Strong analytical and problem-solving skills, with the ability to independently develop algorithm solutions for real-world business needs.

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