Machine Learning Engineer - Speech
Summary Posted: May 28, 2026 Role Number: 200665627-0865 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. Description We are seeking a passionate and experienced Machine Learning Engineer to join our team. In this role, you will push the boundaries of on-device speech recognition and NLP, working across the full stack - from data pipelines and model training to optimization for Apple silicon. You'll collaborate with world-class researchers and engineers to ship technology that reaches hundreds of millions of users, while upholding Apple's unwavering commitment to privacy. Responsibilities Work with unique, proprietary datasets - developing algorithms to process them and devising metrics to evaluate and improve quality Design and implement machine learning models spanning speech recognition and NLP domains Drive data quality insights and influence the design of our end-to-end system Conduct both cutting-edge research and product-oriented development Collaborate closely with researchers, engineers, and product teams to bring new capabilities to life Minimum Qualifications M.Sc. in Computer Science or a related field, or equivalent practical experience Deep understanding of Machine Learning fundamentals Proficiency in Python and at least one deep learning framework (PyTorch, TensorFlow, or JAX) 3+ years of industry experience in deep learning through applied research roles Hands-on experience with the full deep learning lifecycle at scale, including dataset curation, architecture design, distributed training, error analysis, and production deployment. M.Sc. in Computer Science or a related field, or equivalent practical experience Preferred Qualifications Ph.D. in Computer Science or a related field Advanced background and hands-on experience in speech technology (e.g., ASR, TTS, speaker recognition) Background in NLP, including language modeling, text processing, and linguistic understanding Experience training large models using both supervised and self-supervised methods Track record of shipping ML features in a production environment At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong. Learn about accessibility in Apple’s workplace