Machine Learning Engineer, Siri Attention & Invocation

Apple
Cupertino, United States of America2026-04-16

About the job

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.

Responsibilities

Develop and advance frictionless voice invocation experiences.

Be responsible for developing and integrating Siri’s speech and audio experience in a full range of Apple devices.

Collaborate with researchers to develop advanced machine learning (ML) technologies.

Focus on improving the ML training and evaluation infrastructure for improved research efficiency, and faster modeling iterations.

Develop agile deployment processes which are easier to scale using the best automation practices.

Qualifications

Minimum

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

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