Computer Vision Engineer

Job description

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. Good knowledge on software configuration management systems * Strong business acumen, strategy and cross-industry thought leadership * Awareness of latest technologies and Industry trends * Logical thinking and problem solving skills along with an ability to collaborate * Two or three industry domain knowledge * Understanding of the financial processes for various types of projects and the various pricing models available * Client Interfacing skills * Knowledge of SDLC and agile methodologies * Project and Team management