Computer Vision Specialist
14 hours ago
Computer Vision Specialist
Job Description:Kodifly is at the forefront of transforming infrastructure monitoring through advanced spatial intelligence. Our flagship product integrates cutting-edge technologies to provide real-time, actionable insights that enhance the safety, efficiency, and sustainability of infrastructure projects.
Key Responsibilities:- Develop computer vision algorithms for object detection, classification, segmentation, and tracking.
- Implement 3D point cloud processing and SLAM algorithms for real-time applications in mobile and static environments.
- Integrate AI technologies such as Open3D and 2D+3D inference models into our systems for better data analysis and visualization.
- Collaborate with cross-functional teams to integrate new features into SpatialSense.
- Conduct R&D to explore new techniques in computer vision and machine learning.
- Ensure the robustness and accuracy of computer vision applications under various operational conditions.
- Bachelor's, Master's, or Ph.D. in Computer Science, Engineering, or a related field with a specialization in Computer Vision.
- Strong background in 3D point cloud processing, SLAM, point cloud registration, and camera-LiDAR calibration.
- Proficiency in applying deep learning to point cloud data.
- Experience with deep learning frameworks like TensorFlow or PyTorch.
- Skilled in Python and C++ programming.
- Hands-on experience with NVIDIA CUDA, cuDNN, and TensorRT.
- Strong understanding of computer vision concepts such as image processing, feature extraction, object detection, and segmentation.
- Knowledge of OpenCV, PCL, or Dlib.
- Experience with parallel computing and GPU programming is a plus.
- Experience with ROS is highly preferred.
- Strong analytical and problem-solving skills.
- Excellent communication skills and a collaborative mindset.
We offer a collaborative and innovative environment across Pakistan and Hong Kong, competitive salary and share options, and significant professional growth and a chance to impact real-world infrastructure safety and efficiency.
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