Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build, service we create, or Apple Store experience we deliver is the result of us making each other's ideas stronger. That happens because every one of us shares a belief that we can make something wonderful and share it with the world, changing lives for the better. It's the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you'll do more than join something - you'll add something. The Siri Attention & Invocation 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 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 - just by saying '(Hey) Siri.' 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 Attention & Invocation, we own our user journeys end-to-end. We measure the impact of our deployed models not just on pre-ship evaluation sets, but also post-ship on production traffic. We optimize error rates on existing data. We also define new metrics that take into account the user experience we want to deliver 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.
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Industry
Computer and Electronic Product Manufacturing
Education Level
Master's degree
Number of Employees
5,001-10,000 employees