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