Machine Learning Architect Conversational Speech

Join the team redefining what a deeply personal and integrated assistant can part of the Siri organization you will help shape one of the worlds most widely used AI assistants powered by our next-generation of Apple Intelligence with capabilities like personal context understanding and on-screen awareness built with privacy from the ground up. Your work will have direct meaningful impact for users across iOS iPadOS macOS watchOS and is a rare opportunity to build at the intersection of cutting-edge AI and human-centered design shipping technology that is centered around users and their needs.

The Speech organization within Siri drives major speech recognition synthesis and speech-to-speech model advances for features deeply embedded throughout Apples ecosystem. Our mission is to build cutting-edge infrastructure datasets and models that empower Siri conversational AI dictation and speech-enabled Apple Intelligence features across natural language understanding dialog generation speech recognition and multimodal interaction. We apply these technologies to create engaging intelligent and personalized conversational experiences for millions of Apple are seeking a Machine Learning Architect to serve as a senior technical leader spanning the full Speech organization. You will set the future modeling direction for all of conversational speechcharting the architectural and algorithmic course for how Apples speech technologies evolve. You will operate as a hands-on expert who not only defines strategy but also digs into the hardest technical problems working shoulder-to-shoulder with teams to overcome critical obstacles. Reporting directly to the Speech organization leadership you will have broad visibility and influence across speech recognition synthesis dialog multimodal foundation models and speech-to-speech systems ensuring coherent technical vision and cross-team alignment.n

As the Machine Learning Architect for Conversational Speech you will define modeling strategy and technical direction across the Speech organization establishing a unified architectural vision for speech recognition speech synthesis dialog systems multimodal foundation models and speech-to-speech technologies. nYou will serve as the organizations foremost modeling expert providing deep technical guidance to multiple teams working on interconnected speech capabilities. nYou will evaluate emerging research and industry trendsincluding advances in large language models multimodal architectures and full-duplex natural conversational systemsand translate them into actionable roadmaps. nYou will champion production-readiness ensuring architectural decisions account for on-device constraints latency scalability and robustness. nYou will collaborate broadly with partner teams across Siri Apple Intelligence hardware and platform engineering to ensure speech modeling investments are well-integrated into Apples broader AI strategy.n

10 years of experience in machine learning applied to speech or multimodal systems with progressively increasing technical scope and expertise as a technical leader or architect who has defined modeling direction across multiple teams or product hands-on proficiency in modern deep learning including large language models and end-to-end speech experience with multimodal LLMs including architecture design training adaptation and deployment of models that integrate speech audio and text experience building speech-to-speech conversational systems with a strong understanding of full-duplex natural conversational interaction and end-to-end speech track record of translating research into production-quality systems at programming skills in Python and deep learning frameworks such as PyTorch JAX or TensorFlow.

Ph.D. in Computer Science Electrical Engineering Machine Learning or similar technical architecting or leading development of full-duplex natural conversational systems speech-to-speech models or multimodal foundation models that have shipped to large-scale user familiarity with the full stack of speech technologiesASR TTS spoken dialog speaker modeling audio understandingand an ability to reason about their interactions and with large-scale distributed training and the infrastructure considerations that shape model design at data-centric perspective on foundation model development including experience guiding data collection curation annotation and quality with on-device ML deployment including model compression quantization and latency-aware architecture design.n