Play a part in shaping the future of human-computer interaction. Contribute to products that are redefining mobile computing and creating breakthrough technologies in conversational AI, speech recognition, and natural language understanding and generation. Work with the world-class team behind Siri—the intelligent assistant that helps millions of people get things done simply by asking.
The Siri Speech team at Apple is seeking a passionate and experienced Machine Learning Engineer to elevate the Siri experience to new levels of intelligence, fluency, and personalization—empowering users worldwide while upholding Apple’s unwavering commitment to privacy and innovation.
Description
As a Machine Learning Research Engineer on the Siri Speech team, you will help advance Siri’s speech capabilities by focusing on the evaluation, analysis, and improvement of state-of-the-art end-to-end speech models. Your work will play a key role in shaping the next generation of Siri’s understanding and generation systems that power millions of daily interactions.
In this role, you will evaluate emerging Speech LLMs, design and implement novel evaluation frameworks, and develop new tools to measure and enhance model performance. You will analyze model behavior to identify opportunities for improvement in accuracy, robustness, and naturalness. Beyond advancing current models, you will also explore innovative approaches and improve existing algorithms to push the boundaries of what speech models can achieve. You will build efficient automated processes and tooling to streamline large-scale model evaluation and analysis workflows. This position involves close collaboration with cross-functional teams of engineers and researchers from diverse backgrounds, working together in a dynamic and fast-paced environment to deliver high-impact improvements to Siri’s core speech technologies.
Minimum Qualifications
Deep understanding of Machine Learning (ML) fundamentals. Advanced expertise in deep learning, demonstrated through years of industrial roles related to this field as well as publications in relevant conferences, such as Interspeech, ICASSP, ICLR, NeurIPS, etc. Advanced background in speech technologies and related NLP fields. Proficiency in Python and deep learning frameworks such as JAX, PyTorch and TensorFlow.
Preferred Qualifications
Deep technical expertise on Speech LLMs, ASR or TTS. A track record in software design, coding and parallel computing. Proven software development experience, preferably in a deep learning field. Experience with large scale machine learning training/evaluation. Experience in distributed privacy-preserving ML systems.
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