Join our machine learning team at Apple to develop computer vision and localization technologies that help devices understand their place in the world. We're seeking a talented Machine Learning Engineer who excels at transforming research innovations into production-ready solutions, tackling the full spectrum from training large-scale models to optimizing them for real-time, on-device performance. If you're passionate about solving hard problems in spatial intelligence—from challenging real-world environments to privacy-preserving design—this is your opportunity to create experiences that millions of people use every day
As a Machine Learning Engineer on our team, you'll design and implement advanced computer vision solutions that run efficiently on-device, ensuring exceptional performance while respecting user privacy. You'll work across the complete ML lifecycle—from building robust data pipelines and training deep learning models on distributed clusters to optimizing them for Apple's Neural Engine and deploying in production systems. Your work will span critical areas including localization and spatial understanding, where you'll develop systems that enable devices to perceive their position and navigate the world with precision. Your role will bridge cutting-edge research and practical engineering, requiring you to balance innovation with the real-world constraints of shipping products at scale—whether that's ensuring localization works reliably in challenging environments, handling edge cases in visual recognition, or optimizing models to run in real-time on device. Collaborating with world-class researchers, software engineers, and product teams, you'll tackle challenging problems in visual understanding, from place recognition and scene reconstruction to temporal reasoning and multi-sensor fusion. This position offers the unique opportunity to push the boundaries of on-device machine learning, creating spatial intelligence experiences that are not only accurate and responsive but also seamlessly integrated into products that millions of people use every day.