Demonstrated expertise in efficient deep learning with publication record in relevant conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, KDD, ACL, ICASSP, InterSpeech) or a track record in applying efficient deep learning techniques to products Proficient programming skills in Python and one of the deep learning toolkits such as JAX, PyTorch, or Tensorflow PhD in Mathematics or Computer Science, or other technical field, or equivalent industry experience Strong expertise in efficient machine learning, model compression and algorithm optimization techniques A track record in software design, coding and parallel computing Experience with large scale machine learning training/evaluation On-device intelligence and learning with strong privacy protections Ability to work in a collaborative environment. As a researcher on our team, you'll help us advance the state of the art in efficient machine learning for speech and multi-modal modeling, with a strong focus on running advanced models efficiently on server and devices, minimizing latency, preserving privacy and saving energy and bringing your innovations into production.