Computer Vision Architect/ Lead/ Engineer

We are seeking a highly skilled Computer Vision Engineer with hands-on experience in developing and deploying deep learning models for real-time image and video analytics. The ideal candidate will have a strong background in computer vision, deep learning frameworks, and edge deployment technologies. Computer Vision Specialists with hands-on experience in: • Python, PyTorch, TensorFlow • CV/ML/DL model development • Object detection & recognition, Action recognition • NVIDIA technologies • MLOps, Edge deployment Responsibilities: • Design, train, and optimize deep learning models for computer vision tasks such as object detection, image recognition, segmentation, and video analytics. • Lead large-scale real-time implementations involving 100+ video streams. • Fine-tune models like CNNs and Vision Transformers using frameworks such as TensorFlow, PyTorch, and ONNX. • Build and deploy inference pipelines using NVIDIA technologies including NGC models, TAO Toolkit, DeepStream Metropolis, and Triton Server. • Apply pre- and post-processing techniques to enhance model performance and evaluation. • Develop and implement multi-object tracking algorithms across multiple camera feeds., Perform camera calibration and extract regions of interest (ROI), action recognition using temporal analysis techniques. • Develop models for feature extraction and come up with strategies for latent space analysis and manipulation of the data. • Proficiency in writing complex SQL queries, familiarity with NoSQL or Graph Databases (Neo4j) is an advantage. • Knowledge of infrastructure as code tools (e.g., Terraform, Ansible) is an advantage. • Proficiency with containerization technologies (Docker) and orchestration tools (Kubernetes) is an advantage. Preferred Skills: Technology->AI-Data science->Computer Vision,Technology->AI-AI Engineering->MLOps->mlflow,Technology->AI-AI Engineering->AI/ML Solution Architecture and Design,Technology->AI-AI Hyperscalers->Azure Agentic AI Services->Computer Vision with Azure