Siri, let’s work together at Apple!“ The Siri Understanding team is looking for Machine Learning Engineers passionate about enabling personalized Siri interactions and delivering such technology to users on a global scale. Build end-to-end model training and evaluation pipelines. Push the envelope on the latest research developments in speech invocation and speaker recognition. Deploy machine-learned, on-device models that are aligned with the core values of Apple, ensuring the highest standards of quality, innovation, and respect for user privacy. And work with the people who created the intelligent assistant that helps millions of people around the world get things done.

You will be part of a team whose focus is on applied machine learning, on building and deploying models that constantly advance the state-of-the-art. But that is only half the story! In Siri Understanding, we own our products and user experiences end-to-end. We measure the impact of our deployed models not just on offline test sets, but also on production traffic. We optimize error rates on existing data. We also define new metrics and apply them to the data that best represents the next feature we ship. And we are sometimes constrained by the limits of on-device computation — that is where your ability to innovate will be most impactful. You will collaborate with many dynamic, cross-functional teams consisting of software engineers and machine learning engineers/scientists. The ideal candidate will excel in both academic rigor and engineering efficacy, staying up-to-date with the latest research advancements as well as delivering reliable and robust models to all devices for all users around the world. If you are passionate about building outstanding products and using the full spectrum of your skills to extend the core technology that lets Siri understand, personalize, and interact in new and exciting ways, then we cannot wait to hear from you.

Strong background in machine learning and deep learningProficiency in deep learning / machine learning frameworks (e.g., PyTorch, TensorFlow) and scripting languages (e.g., Python, bash), with strong software engineering fundamentals and an interest in optimizing and scaling systems globallyOutstanding problem solving, critical thinking, creativity, and interpersonal skills; ability to communicate effectively with engineers, scientists, managers, and cross-functional partners