Key responsibilities:

1. Develop and train state-of-the-art algorithms to perform visual recognition tasks, such as segmentation, detection, and classification at scale on multi-million image datasets
2. Integrate deep neural networks and the associated preprocessing and postprocessing code to run efficiently on our platform devices, including different GPU architectures
3. Work closely with IT to ensure the development of highly scalable solutions
4. Work closely with product and business teams to ensure strong alignment between AI solutions and customer requirements
5. Optimize production AI models used by enterprise customers and partners

Requirements:

1. Working knowledge of deep learning, machine learning, and statistics
2. Working knowledge in deep learning using convolutional neural networks (CNN), recurrent neural networks (RNN), and LSTM
3. Knowledge of deep learning applications with computer vision, image captioning, video analysis, image manipulation, image segmentation, object detection, and feature mapping
4. Functional expertise in DL modeling practices specific to data at hand (size of the model, training procedures, hand-designed layers, etc.)
5. Thorough understanding of state-of-the-art DL concepts (sequence modeling, attention, convolution, etc.) along with a knack to imagine new schemas that work for the given data
6. NLP expertise, especially in language modeling, experience in using pre-trained language models (transformer/GPT/BERT)
7. Degree in statistics, applied mathematics, or a related discipline
8. Professional deep learning training certifications

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