Computer Vision Engineer
3 weeks ago
Enhance and optimize SLAM algorithms for real-time application in mobile and static environments.
Integrate and optimize AI technologies such as Open3D and 2D+3D inference models into our existing systems for improved 2D & 3D data analysis and visualization.
Collaborate with cross-functional teams in Pakistan and Hong Kong to integrate new features into SpatialSense.
Conduct R&D to explore new techniques in computer vision and machine learning that can improve infrastructure monitoring.
Ensure the robustness and accuracy of our computer vision applications under various operational conditions
Design and develop computer vision algorithms and models for various applications, including object detection, image classification, segmentation, and tracking.
Optimize computer vision algorithms and models to leverage the power of NVIDIA hardware, such as GPUs and specialized accelerators (e.g., NVIDIA Tensor Cores).
Collaborate with hardware engineers and architects to explore and utilize the latest features and capabilities of NVIDIA hardware platforms.
Conduct performance profiling and benchmarking of computer vision algorithms on NVIDIA hardware to identify bottlenecks and optimize resource utilization.
Implement and integrate computer vision algorithms into end-to-end systems, ensuring scalability, robustness, and real-time performance on NVIDIA hardware.
Collaborate with researchers and academic partners to explore and evaluate state-of-the-art computer vision techniques and their application on NVIDIA hardware.
Qualifications:Bachelors, Masters or Ph.D. in Computer Science, Engineering, or related field with a specialization in computer vision.
Strong background in 3D point cloud data processing, including experience with SLAM, point cloud registration, and camera-LiDAR calibration.
Proficiency in applying deep learning methods to point cloud data.
Strong expertise in deep learning frameworks, such as TensorFlow or PyTorch, and proficiency in programming languages like Python and C++.
Extensive experience in optimizing computer vision algorithms for NVIDIA hardware, including GPUs and specialized accelerators (e.g., NVIDIA Tensor Cores).
In-depth understanding of computer vision concepts, including image processing, feature extraction, object detection, and segmentation.
Hands-on experience with NVIDIA CUDA and cuDNN libraries, as well as frameworks like TensorRT for efficient deployment on NVIDIA hardware.
Knowledge of parallel computing principles and GPU programming techniques is a plus.
Familiarity with computer vision libraries and tools, such as OpenCV, Dlib, or PCL.
Strong problem-solving and analytical skills, with the ability to optimize algorithms for performance and accuracy on NVIDIA hardware.
Experience with ROS software and methodologies.
Proficient in programming languages such as C++, Python, or similar.
Knowledge of machine learning and deep learning frameworks like TensorFlow or PyTorch.
Excellent analytical, problem-solving, and communication skills.
Team-oriented with an ability to work in a collaborative environment.
We Offer:Opportunity to work with state-of-the-art technology in a rapidly evolving field.
A collaborative environment where innovation is encouraged and rewarded.
Competitive salary and share options.
Professional and personal growth opportunities and a chance to make a significant impact in infrastructure safety and efficiency.
Join Us at Kodifly:
If you're ready to apply your computer vision skills to tackle real-world challenges and drive technological advancement, Kodifly is looking for you. Apply now and begin your journey at the cutting edge of infrastructure technology
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