Train machine learning and deep learning models on a computing cluster for visual recognition & perception tasks, such as segmentation and detection and world representation applications
Develop state-of-the-art algorithms in one or all of the following areas: deep learning (convolutional neural networks), object detection/classification, tracking, multi-task learning, large-scale distributed training, multi-sensor fusion, dense depth estimation, LLMs, etc.
Optimize deep neural networks and the associated preprocessing/postprocessing code to run efficiently on an embedded device
What You’ll Bring
Experience writing both production-level Python (including Numpy and Pytorch) and modern C++.
Experience in deep imitation learning or reinforcement learning in realistic applications
Exposure to robotics learning through tactile and/or vision-based sensors
Proven track record of training and deploying real world neural networks
Familiarity with 3D computer vision and/or graphics pipelines