On-Device Machine Learning Engineer

Were starting to see the incredible potential of multimodal foundation and large language models and many applications in the computer vision and machine learning domain that previously appeared infeasible are now within reach. We are looking for a highly motivated and skilled Machine Learning Integration Engineer to join our team in the Video Computer Vision group and help us ship cutting edge computer vision technology on Apple devices. The Video Computer Vision org has pioneered features such as FaceID FaceKit and Gaze and Hand gesture control which have changed the way millions of users interact with their devices. We balance research and product requirements to deliver Apple quality pioneering experiences innovating through the full stack and partnering with HW SW and AI teams to shape Apples products and bring our vision to life.

As part of the Video Computer Vision (VCV) team you will deploy purpose-built vision models on Apple devices developing innovative techniques to optimize their performance efficiency and scalability on-device.

Convert and integrate foundation models for on-device power and performance of models running on Apple on-device inference latency and efficiency of CV/ML models.

BS and a minimum of 10 years relevant industry knowledge of model compression techniques such as pruning distillation quantization and weight understanding of operating system and extensive programming experience in Python and working with with machine learning model development lifecycle including data preprocessing model training evaluation and understanding of machine learning: MultiModal LLMs and integration of ML components into production systems.

Experience with CoreFoundation RealityKit and CoreML knowledge of real-time video pipelines image transformations and rendering experience with Swift.