Computer Vision Architect/ Lead/ Engineer

* 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.

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