Machine Learning Engineer, Speech Products

We're seeking engineers excited about applying machine learning to build and maintain the core ML products behind Apple's speech technologies. You'll join a highly technical, collaborative team of ML, software, and infrastructure experts to develop systems used by millions of people.

This role offers the chance to work on impactful projects across Apple and to apply your ML, data science, and analytical skills to solve complex problems and deliver innovative user-facing products.

Join a pivotal team that builds the automation and scalable infrastructure that carries Apple's speech research into production for millions of users. We design and maintain the training and evaluation pipelines that enable rapid experimentation, robust model validation, and seamless deployment of next-generation speech technologies. In this role, you will engineer and refine the systems that transform research ideas into reliable, production-ready modeling workflows.

You'll improve automation, ensure high-quality model behavior at scale, and create the frameworks that accelerate model development across the speech organization. Your work forms the backbone of Apple's state-of-the-art speech capabilities-powering technologies that reach our users around the world.

Hands-on experience with distributed compute and data systems (Spark, Ray) Working knowledge of speech/ASR/TTS concepts (audio features, tokenization, speech augmentation, alignment, evaluation metrics) Comfort working cross-functionally with research scientists, data engineers, and product teams

Experience designing, building, and maintaining scalable ML pipelines for training, evaluation, and continuous monitoring. Strong software engineering skills, with proficiency in Python Solid understanding of core ML concepts, such as supervised/unsupervised learning, model evaluation, and performance analysis. Strong verbal and written communication skills Bachelor's or graduate degree in Computer Science, Computer Engineering, or a related field, or equivalent experience