Generative AI enables us to rethink the way we use our devices. Play a part in the next revolution in human-computer interaction. Work with the people behind Shortcuts & App Intents, Apple Intelligence, and other system experiences that help millions of people get things done!

The Shortcuts & App Intents team is looking for an experienced applied machine learning scientist passionate about transformative new computing experiences powered by generative AI. Work at the intersection of cutting-edge machine learning research, software engineering, and Human Interface Design.

In this role, you will bootstrap and lead machine learning research and application in our group and drive model development and experimentation from concept to production. Responsibilities will include training large scale models on distributed backends, deployment of compact neural architectures efficiently on device, and addressing safety challenges to make our models robust and aligned with human values. As a creative problem solver who excels when faced with new ambiguous problems, you will help us shape our roadmap and solve significant technical challenges in new spaces.

An ideal candidate for this role will have industry experience in program synthesis and Large Language Models (LLMs), as well as knowledge of other contemporary modeling problems (e.g., Conversational Agents, Sequential Decision Making, Reinforcement Learning, Autonomous Systems, Human Preference Learning), along with a proven track record of shipping products and experiences. You will work across teams and organizations spanning a variety of disciplines, collaborating closely with machine learning researchers, software engineers, hardware and design teams.

3+ years of industry experience with strong machine learning fundamentalsAn advanced degree (Master’s) in Computer Science, Artificial Intelligence, Machine Learning, or a related experience is requiredStrong analytical and problem solving skillsStrong programming skills in Python, C and C++, proficiency in using machine learning toolkits, e.g., PyTorchHands-on experience with building Deep Learning applications