Machine Learning Systems Engineer – Video Computer Vision

As a member of the Video Computer Vision team, you will train, evaluate, and deploy purpose-built vision models on Apple hardware. You will develop innovative techniques to optimize model performance, efficiency, and scalability, ensuring a seamless user experience under strict on-device constraints. Bachelor’s degree in Computer Science, Machine Learning, or a related discipline, and 3+ years of relevant industry experience. Strong ML fundamentals. A proven track record of writing high-quality production code for shipped CV/ML features. Solid understanding of operating system fundamentals and extensive programming experience in Python and C++. Hands-on experience with PyTorch and familiarity with the end-to-end ML lifecycle (data preprocessing, training, evaluation, and edge deployment). Experience with Supervised Fine-Tuning (SFT) pipelines to adapt vision and multimodal foundation models for specialized, on-device downstream tasks. Robust foundational understanding of machine learning architectures, specifically Multimodal LLMs and the integration of ML components into complex production systems. Programming experience with Swift and familiarity with CoreML, CoreFoundation, and RealityKit frameworks. Fundamental knowledge of real-time video pipelines, image transformations, and rendering loops. Experience optimizing models for neural network accelerators (e.g., Apple Neural Engine or mobile GPUs).