Computer Vision Engineer

Should have the hands on experience to train computer vision and deep learning models to solve computer vision use cases.
* Should be able to create and optimize algorithms for image and video analysis, for tasks such as object detection, image recognition, segmentation and video analytics.
* Should have expertise on different object tracking algorithms and track multi objects in multi cameras.
* Should be able to articulate camera calibration and region of interest extraction.
* Should have experience working on a large-scale implementation with 100+ stream in real time
* Fine-tune deep learning models like CNNs, vision transformers using frameworks such as Tensorflow, PyTorch, onnx etc.
* Should have used NVIDIA frameworks preferably like NGC models, TAO toolkit, metropolis Deep stream, triton server, and triton server to create inferencing pipeline and its deployment.
* Should have knowledge of optimizing inferencing pipelines to work on edge
* Should be able to perform necessary pre and post processing to optimize the computer vision models and evaluate it.
* Should have experience working on action recognition with temporal analysis
* Should have knowledge on pruning the model for deploying on edge/ARM devices
* Collaborate with Business and IT teams

Computer Vision modeler who will develop real-time computer vision models like
* Python, Pytorch, tensorflow
* CV/ML model development
* Object recognition/Detection
* NVIDIA technologies
* MLOps