Proactive Intelligence is at the heart of an intelligent system experience that understands you and anticipates your needs. We are building an on-device personal and contextual intelligence platform that will benefit the millions of people who use Apple devices every day. We want your help to use state-of-the-art machine learning to build a personal context platform that captures your past, current, and future activities, environment, and intentions to power next generation personal assistants and experiences.

As a part of this team, you will touch various parts of our codebase, from researching and experimenting with new ideas to fine-tuning large language models that will be deployed on-device. You will have the opportunity to teach and learn from others and grow in our close-knit, growing team!

You’ll join a phenomenal team of hardworking software engineers, ML engineers and Generative AI researchers on the Contextual Understanding Team. The team is responsible for providing Siri and other clients with on-screen, conversational, and environmental context to power the next generation of personal context use cases in Siri. We’re looking for a Senior ML Engineer with a focus on Generative AI who will be responsible for building scalable synthetic data generation pipelines, and fine-tuning large language models to solve complex tasks in the space of UI understanding. You will solve problems and deploy solutions that enable users to use Siri to naturally take action over what they are looking at on-screen!

M.S. or PhD in Computer Science or related field, or equivalent practical experience5+ years of industry experience developing, training, and fine-tuning machine learning models offline using Python, with a strong understanding of machine learning algorithms, frameworks (e.g. Pytorch, Scikit-learn) , and data preprocessing techniquesDemonstrated experience applying generative AI techniques to solve complex problems, with a strong understanding of the underlying technologiesProven ability to train and debug deep learning systems: building datasets, training models, defining metrics, and performing error analysisStrong software engineering skills in Python to build scalable and robust infrastructure for deep learning data, modeling, and evaluation systems