
SLAM Algorithm Developer
24 hours ago
About Kodifly:
Kodifly is revolutionizing infrastructure monitoring through innovative spatial intelligence. With a strong presence in Hong Kong Science Park and collaborations with leading institutions, we specialize in 3D point cloud processing, digital twin creation, and LiDAR technology. Our flagship product, SpatialSense, combines these advancements to provide real-time insights enhancing infrastructure safety, efficiency, and sustainability.
Job Role:
We are seeking a highly skilled 3D Computer Vision Engineer to join our team in Islamabad, Pakistan. This position requires expertise in point cloud data processing, SLAM, point cloud registration, camera-LiDAR calibration, and deep learning techniques to empower smart cities.
Key Responsibilities:
- Algorithm Development: Design and implement algorithms for 3D point cloud processing, object recognition, and segmentation.
- SLAM Algorithm Optimization: Enhance and optimize SLAM algorithms for real-time application in mobile and static environments.
- System Integration: 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.
- Cross-Functional Collaboration: Collaborate with cross-functional teams in Pakistan and Hong Kong to integrate new features into SpatialSense.
- R&D: Conduct R&D to explore new techniques in computer vision and machine learning that can improve infrastructure monitoring.
- System Robustness: Ensure the robustness and accuracy of our computer vision applications under various operational conditions
- Model Development: Design and develop computer vision algorithms and models for various applications, including object detection, image classification, segmentation, and tracking.
- Hardware Optimization: Optimize computer vision algorithms and models to leverage the power of NVIDIA hardware, such as GPUs and specialized accelerators (e.g., NVIDIA Tensor Cores).
- Collaboration: Collaborate with hardware engineers and architects to explore and utilize the latest features and capabilities of NVIDIA hardware platforms.
- Performance Analysis: Conduct performance profiling and benchmarking of computer vision algorithms on NVIDIA hardware to identify bottlenecks and optimize resource utilization.
- End-to-End Integration: Implement and integrate computer vision algorithms into end-to-end systems, ensuring scalability, robustness, and real-time performance on NVIDIA hardware.
- Research Collaboration: Collaborate with researchers and academic partners to explore and evaluate state-of-the-art computer vision techniques and their application on NVIDIA hardware.
Requirements:
- 3+ years of experience
- 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.
What We Offer:
- Opportunity to work with cutting-edge 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.
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