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Generative AI Research Engineer, Siri Speech

Apple· Machine Learning and AI
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Hybrid (Cambridge)Full-timePosted 1w ago

About the role

Early career Research Engineer on the Siri Speech (TTS) Team focused on advancing generative speech models, on-device integration, and controllable synthesis for Apple devices. Collaborates with cross-functional teams to develop and benchmark novel generative AI techniques for on-device speech synthesis, emphasizing steerability, expressiveness, and fine-grained control of large language models and generative speech decoders.

Responsibilities

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

Qualifications

  • Deep Learning Foundations: Strong theoretical background in modern deep learning architectures, sequence modeling, and generative AI frameworks (e.g., Transformers, Flow Matching, Diffusion, VAEs).
  • Mathematical Rigor: Solid foundation in optimization, probability theory, linear algebra, and statistical machine learning.
  • Engineering Excellence: Excellent programming skills in Python and PyTorch, with experience writing clean, scalable code for model training and inference.
  • On-Device & System Awareness: Exposure to or strong interest in efficient model execution, quantization, and deployment constraints for edge/on-device computing.
  • Research Mindset: Strong problem-solving abilities, high curiosity, and a passion for exploring novel frontiers in speech and language modeling.
  • Degree: Master’s degree (MSc) or equivalent in Computer Science, Mathematics, Data Science, Physics, or a related quantitative field.
  • Experience: Early career — post-degree experience or practical industry/academic research experience demonstrated through publication, open-source codebases, or high-impact projects.

Skills

Required:Deep learning theoryOptimization and mathematicsPythonPyTorch
Last updated Oct 16, 2026. Interested? Apply on the company site.

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