Q - Audio Machine Learning Engineer

Summary Our team is new, growing, and evolving quickly, and we are hiring across multiple disciplines. We work at the intersection of machine learning, hardware, and software, creating technologies that reshape how people communicate and experience the world around them in everyday life. Description Apple's Hardware group is home to some of the world's most advanced technologies - powering the experiences that define Apple products. We are looking for a talented and curious Audio Machine Learning Engineer to join our growing Machine Learning team in Herzliya. In this role, you will help create the full data lifecycle that underpins our models: from designing what data we collect, through curation and quality monitoring, to running rigorous experiments that drive model improvements. You will work closely with other ML and Data Engineering teams to ensure our models are trained on the best possible data, reaching the best accuracy, and that we deeply understand when and why they don't perform as expected. In this role, you will push the boundaries of audio solutions 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. You'll redefine the future of human-computer interaction and the way people communicate and contribute to products that shape mobile computing and create breakthrough technologies in the audio domain. Minimum Qualifications BS or MS in CS, EE, or related degree 3+ years of industry experience in deep learning through applied research roles Deep understanding of Machine Learning fundamentals Proficiency in Python and at least one deep learning framework (PyTorch, TensorFlow, or JAX) Collaborative skills for dependable and consistent steering of novel research alongside fellow teams Preferred Qualifications Ph.D. in CS, EE or a related field Advanced background and hands-on experience in speech ML technology (e.g., multi-modals, speaker embeddings, voice isolation, ASR, multichannel sensor fusion, generative speech) Background in digital signal processing (DSP) for audio signals 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