OpenNash Jobs
Apple

Senior Machine Learning Research Engineer, AIML

Cupertino, United States of AmericaSenior individual contributorData & Analytics

Listed on Apple’s official careers site. Posted June 4, 2026. Check that it is still open and apply there.

Apply on Apple’s careers site →

Job description

Are you passionate about Generative AI and excited to work on groundbreaking modeling technologies that will enrich the lives of billions? The AIML team within Apple's software organization is a multidisciplinary group operating at the intersection of Multimodal Foundation Models, Efficient and Scalable ML Infrastructure, and Personalized Intelligent Experiences. As a senior machine learning engineer on our team, you will design software systems and algorithms that enable performant, scalable training and inference for Apple's AI-driven experiences across both on-device and server environments.

This role also includes opportunities to open source your work. Join our team of highly skilled, impact-focused engineers!

More jobs at Apple

AI Data & Infrastructure Engineer

Cupertino, United States of America

AI Data & Knowledge Engineer

Cupertino, United States of America

AI Data Platform Engineer

Cupertino, United States of America

AI/ML Engineer: System RF Data Ecosystem

Cupertino, United States of America

Similar jobs at other companies

Research Intern - Machine Learning for Biology and Healthcare

Microsoft · United States, Massachusetts, Cambridge

Research Intern - Machine Learning and Statistics

Microsoft · United States, Massachusetts, Cambridge, Washington, Redmond

Senior Machine Learning Engineer

CVS Health · New York, NY

A/AI Machine Learning Engineer

Lockheed Martin · Manassas, VA

Senior Staff Engineer, Machine Learning Engineering ( On-device Learning SW )

Qualcomm · San Diego, California, United States of America

OpenNash lists jobs from employers’ own careers sites and does not handle applications. Dates come from the employer where stated; “first seen” and “last checked” are our own observations.