Sr. Machine Learning Research Engineer, Siri Speech

We are a group of engineers/researchers responsible for advancing Siri Conversational AI at Apple. Our mission is to build cutting-edge infrastructure, datasets, and models that empower Siri with powerful general capabilities across natural language understanding, dialog generation, speech synthesis and recognition, and multi-modal interaction. We apply these technologies to create engaging, intelligent, and personalized conversational experiences for millions of Apple users!

We believe that the most impactful breakthroughs in deep learning emerge when we address real-world problems at scale while we preserve user privacy. Siri presents a unique and rich set of challenges-from robust understanding of diverse user intents to fluid, contextual, and trustworthy multi-turn dialog. Join us, and we will take on the challenges to push the frontiers of foundation models and conversational AI!

On the Siri team, you will work alongside a fast-growing team of world-class engineers and scientists to tackle core problems in efficient machine learning for effective dialog systems and foundation models-ranging from natural language understanding and multi-turn context tracking, to the integration of speech, text, and other modalities.

You will develop and deploy novel deep learning technologies that make Siri more intelligent, natural, and useful. You will see your ideas not only published in papers, but also improve the experience of millions of users.

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. Your ideas will directly impact the daily lives of billions of users through Siri.

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