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Infosys brand plus metro location create moderate competition despite niche computer-vision skills.
Highly specialized computer vision and edge deployment skills limit cross-industry transferability.
Multiple mandatory specialized ML, NVIDIA, edge deployment, and MLOps skills indicate strict technical filters.
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Design, train, and optimize deep learning models for computer vision tasks including object detection, image recognition, segmentation, and video analytics.
Lead large-scale real-time implementations managing 100 video streams.
Build and deploy inference pipelines using NVIDIA technologies such as NGC models, TAO Toolkit, DeepStream, Metropolis, and Triton Server.
Hands-on experience developing and deploying deep learning models for computer vision, specifically with Python, PyTorch, and TensorFlow.
Experience in object detection, recognition, and action recognition in video analytics.
Familiarity with NVIDIA AI deployment technologies (NGC models, TAO Toolkit, DeepStream, Triton Server).
Work Experience Required: Not explicitly mentioned in the JD.
Experience leading real-time computer vision projects at scale involving multiple video streams (100+).
Skilled in optimizing and fine-tuning CNNs and Vision Transformer models using PyTorch, TensorFlow, and ONNX.
Additional experience with MLOps tools, containerization (Docker, Kubernetes), infrastructure as code (Terraform, Ansible), and advanced databases (NoSQL, Neo4j) is advantageous but not mandatory.