Generative AI Research Engineer, Siri Speech

Be part of the next revolution in human-computer interaction. Contribute to products that are redefining mobile computing. Create groundbreaking technology for large-scale systems speech synthesis and generative artificial intelligence. Work with the team building the intelligent assistant that helps millions of people get things done every day.

The Siri Speech (TTS) Team is seeking a highly qualified creative and hands-on Early Career Research Engineer eager to advance the state-of-the-art in generative speech models and improve the user experience across Apple this role you will collaborate with world-class product and research teams to integrate novel generative AI paradigms into on-device user a Research Engineer on the End-to-End Neural TTS team your primary focus will be researching and developing techniques to enhance the steerability expressiveness and fine-grained control of Large Language Models and Generative Speech Decoders on Apple devices.

Investigate innovative conditioning alignment and guided inference methods to reliably control attributes such as prosody emotion speaker identity and pacing in generative audio pipelines. nBuild proof-of-concept prototypes benchmark new algorithmic approaches and write high-quality software libraries to bridge cutting-edge research with production capabilities. u2028nCollaborate across multidisciplinary teams to ensure next-generation speech synthesis technology runs efficiently reliably and accessibly for everyone everywhere. u2028nAdapt quickly to evolving research trends and shifting priorities in a fast-paced environment.

Deep Learning Foundations: Strong theoretical background in modern deep learning architectures sequence modeling and generative AI frameworks (e.g. Transformers Flow Matching Diffusion VAEs). u2028nMathematical Rigor: Solid foundation in optimization probability theory linear algebra and statistical machine learning. u2028nEngineering Excellence: Excellent programming skills in Python and PyTorch with experience writing clean scalable code for model training and inference. u2028nOn-Device u0026 System Awareness: Exposure to or strong interest in efficient model execution quantization and deployment constraints for edge/on-device computing.u2028

Research Mindset: Strong problem-solving abilities high curiosity and a passion for exploring novel frontiers in speech and language modeling. u2028nDegree: Masters degree (MSc) or equivalent in Computer Science Mathematics Data Science Physics or a related quantitative field. u2028nExperience: Early career: post-degree experience or practical industry/academic research experience demonstrated through publication open-source codebases or high-impact projects