• Stay up to date with the latest research and innovations in deep learning, implement and experiment with new ideas. • Foster collaborative partnerships with our researchers and engineers, transforming innovative research into robust, industrial-strength machine learning models. • Taking approaches from initial evaluation and experimentation all the way to shipping. • Defining and collecting training datasets. • Building training pipelines and real-time inference run-times (PyTorch, TensorFlow, TensorRT, Python, C++).