Sr. Machine Learning Scientist, Siri Speech

About the role

You will work alongside a fast-growing team of world-class engineers and scientists to tackle core problems in 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'll help us advance the state of the art in natural language processing, speech and audio modeling, and multi-modal learning, with a strong focus on bringing your innovations into production. Your ideas will directly impact the daily lives of billions of users through Siri.

Requirements

• Bachelor's, Master's, or PhD in Computer Science or other related disclipline
• Experience with conversational AI or multimodal LLM
• Experience with large scale machine learning training/evaluation
• Data-centric vision about foundation model
• Demonstrated expertise in 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 deep learning techniques to products
• Proficient programming skills in Python and one of the deep learning toolkits such as PyTorch, JAX, or Tensorflow","internalDetails":null
• Pay & Benefits
• Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Additional Information

The Speech Team within the Siri organization drives major speech recognition, synthesis and speech to speech model changes for various features deeply embedded throughout Apple's ecosystem. Our mission is to build cutting-edge infrastructure, datasets, and models that empower Siri conversational AI, dictation and various speech enabled Apple Intelligence features with powerful capabilities across natural language understanding, dialog generation, speech 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. We develop speech to speech experiences and the underlying multimodal foundation model technology for current and future speech-enabled features across Apple's software, hardware, and services ecosystem. This allows for cutting edge applied research anchored in Apple specific production needs, while improving speech interaction experiences for Apple's customers around the world.

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