Sr. Computer Vision

Role Overview: As a Senior Computer Vision Machine Learning Engineer at Codvo, you will be responsible for architecting, developing, and deploying high-performance computer vision systems for real-time applications. Your deep expertise in object detection, segmentation, tracking, and pose estimation, along with experience in optimizing and deploying deep learning models on edge platforms, will be crucial for the success of our projects. Key Responsibilities: - Design, develop, and optimize computer vision models for: - Object Detection - Image & Instance Segmentation - Multi-Object Tracking - Human Pose Estimation - Build and train deep learning models using frameworks such as PyTorch or TensorFlow. - Convert and optimize models for edge deployment using: - TensorRT - OpenVINO - NVIDIA TAO Toolkit - Perform model quantization, pruning, benchmarking, and latency optimization. - Deploy models on edge hardware platforms (NVIDIA Jetson, Intel-based edge devices, NVIDIA IGX Orin, etc.). - Write clean, scalable, and production-ready Python code. - Collaborate with cross-functional teams including ML engineers, software developers, and hardware teams. - Conduct performance evaluation, debugging, and continuous improvement of deployed systems. - Stay updated with the latest research and advancements in computer vision and edge AI. Qualification Required: - 5+ years of hands-on experience in Computer Vision and Deep Learning. - Strong expertise in: - Object detection architectures (e.g., YOLO, Faster R-CNN, SSD) - Segmentation models (e.g., U-Net, Mask R-CNN) - Tracking algorithms (e.g., DeepSORT, ByteTrack) - Pose estimation frameworks (e.g., OpenPose, HRNet) - Proven experience deploying optimized models using: - TensorRT - OpenVINO - NVIDIA TAO Toolkit - Strong Python programming skills. - Experience with model optimization techniques (INT8 quantization, FP16, pruning). - Familiarity with ONNX and model conversion pipelines. - Strong understanding of GPU acceleration and edge hardware constraints. Role Overview: As a Senior Computer Vision Machine Learning Engineer at Codvo, you will be responsible for architecting, developing, and deploying high-performance computer vision systems for real-time applications. Your deep expertise in object detection, segmentation, tracking, and pose estimation, along with experience in optimizing and deploying deep learning models on edge platforms, will be crucial for the success of our projects. Key Responsibilities: - Design, develop, and optimize computer vision models for: - Object Detection - Image & Instance Segmentation - Multi-Object Tracking - Human Pose Estimation - Build and train deep learning models using frameworks such as PyTorch or TensorFlow. - Convert and optimize models for edge deployment using: - TensorRT - OpenVINO - NVIDIA TAO Toolkit - Perform model quantization, pruning, benchmarking, and latency optimization. - Deploy models on edge hardware platforms (NVIDIA Jetson, Intel-based edge devices, NVIDIA IGX Orin, etc.). - Write clean, scalable, and production-ready Python code. - Collaborate with cross-functional teams including ML engineers, software developers, and hardware teams. - Conduct performance evaluation, debugging, and continuous improvement of deployed systems. - Stay updated with the latest research and advancements in computer vision and edge AI. Qualification Required: - 5+ years of hands-on experience in Computer Vision and Deep Learning. - Strong expertise in: - Object detection architectures (e.g., YOLO, Faster R-CNN, SSD) - Segmentation models (e.g., U-Net, Mask R-CNN) - Tracking algorithms (e.g., DeepSORT, ByteTrack) - Pose estimation frameworks (e.g., OpenPose, HRNet) - Proven experience deploying optimized models using: - TensorRT - OpenVINO - NVIDIA TAO Toolkit - Strong Python programming skills. - Experience with model optimization techniques (INT8 quantization, FP16, pruning). - Familiarity with ONNX and model conversion pipelines. - Strong understanding of GPU acceleration and edge hardware constraints.