Machine Learning Engineer

3-5 years of experience with scalable machine learning technologies

Strong background in machine learning and deep learning; experience in speech recognition is highly desired

Proficiency in deep learning / machine learning frameworks (e.g., PyTorch, TensorFlow) and programming languages including but not limited to C/C++/Python, with strong software engineering fundamentals and an interest in optimizing, automating, and scaling end-to-end systems (e.g., PySpark, Airflow)

Strong attention to detail, along with the analytical skills and the willingness to dive into data to explain anomalies and conduct error/deviation analyses

Outstanding problem solving, critical thinking, creativity, and interpersonal skills; ability to communicate effectively and to work well in multi-functional teams

Preferred Qualifications

Master's or Ph.D. degree in Computer Science, Electrical Engineering or related field; outstanding candidates with Bachelor's degrees and multiple years of significant engineering/product experience will also be considered

Industry experience in product development and deployment and understanding of full software product life cycle

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. "Hey Siri, let's work together at Apple!\\" The Siri Attention & Invocation team is looking for Machine Learning Engineers passionate about developing and advancing frictionless voice invocation experiences on Apple's innovative devices, enabling compelling new conversational features for Siri interactions. Build end-to-end model training and evaluation pipelines. 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 will be 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. 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. "Hey Siri, let's work together at Apple!" The Siri Attention & Invocation team is looking for Machine Learning Engineers passionate about developing and advancing frictionless voice invocation experiences on Apple's innovative devices, enabling compelling new conversational features for Siri interactions. Build end-to-end model training and evaluation pipelines. 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.'