Senior Computer Vision Engineer in SAUDI ARABIA

Title: Computer Vision Engineer | KSA / Remote

Tech Stack: Python, C++, OpenCV, PyTorch, TensorFlow, Keras, Dlib, YOLO, Faster R-CNN, ResNet, Mask R-CNN, CUDA, Docker, Git, AWS/GCP/Azure

What You’ll Do:

Join an R&D-heavy team solving complex real-world problems through advanced computer vision and machine learning. You'll develop and optimize algorithms for real-time video/image analysis, including object detection, segmentation, and classification. Expect hands-on work with model training, optimization for edge/cloud environments, and tight collaboration with data, product, and engineering teams. You'll also prototype new solutions and help integrate vision models into production systems used in mission-critical applications.

Who They Are:

An innovation-first product company working at the frontier of AI and vision intelligence. Their platform is used in next-gen hardware and smart infrastructure across various sectors. With a focus on cutting-edge research and real-world impact, they offer a fast-paced and intellectually stimulating environment where engineers have real influence on product direction.

Benefits

• Salary 35 - 45k SAR
• Visa and medical insurance
• Relocation support
• Career growth

Requirements

• 5+ years in computer vision, with hands-on experience across detection/classification/segmentation models
• Strong experience with deep learning frameworks (TensorFlow, PyTorch, Keras), OpenCV, and classical image processing
• Proficient in Python and/or C++
• Experience with cloud-based deployment (AWS, GCP, or Azure), Docker, and GPU acceleration (CUDA)
• Solid grasp of ML techniques including CNNs, transfer learning, model optimization, and training at scale
• Familiarity with camera calibration, 3D vision, and optical flow
• Bachelor's or Master’s in CS, AI, or a related field

Bonus

• Worked on edge devices (Jetson, Coral), SLAM, or sensor fusion (LIDAR, radar)
• Published papers, patents, or contributions to open-source CV/ML projects
• Experience in real-time video processing or multi-threaded systems