Cambridge, England, United Kingdom Machine Learning and AI
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 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!
Description
On the Siri team, you will work alongside a fast-growing team of extraordinary engineers and scientists to solve 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 billions of users.As a researcher on our team, you’ll help us advance the state of the art technology for speech and multi-modal modeling. With a focus on running advanced models efficiently on server and devices: minimizing latency, preserving privacy, saving energy and bringing your innovations into production.
Minimum Qualifications
- Proven expertise in efficient deep learning with publication record in 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
- Masters Degree or PhD in Mathematics or Computer Science, or other technical field, or equivalent industry experience
Preferred Qualifications
- Strong expertise in 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
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