Computer vision Engineer

n 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.

The job entails sitting as well as working at a computer for extended periods. Should be able to communicate by telephone, email or face to face.

Estimated annual compensation range for the candidate based in the below location will be for Ontario $92004 to $123375.