Machine Learning Systems Engineer – Video Computer Vision

Apple • Sunnyvale, CA

20h • Onsite

About The Position

The Video Computer Vision (VCV) group is looking for a highly motivated and skilled Machine Learning Systems Engineer to help us ship cutting-edge computer vision technology on Apple devices. The VCV organization has pioneered groundbreaking features like FaceID/FaceKit, Gaze/Hand Gesture Control, Body Tracking, and 2D/3D Scene Understanding fundamentally changing how millions of users interact with technology. We seamlessly balance research and product requirements to deliver pioneering, Apple-quality experiences. By innovating across the full stack and partnering closely with hardware, software, and AI teams, we shape future products and bring our architectural vision to life. 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. Develop on-device software that bridges multimodal AI models and computer vision technologies with production systems deployed across Apple devices. Optimize on-device inference latency, memory footprint, and computational efficiency of CV/ML models. Benchmark, profile, and evaluate the power consumption and thermal performance of models running on Apple silicon.

Requirements

• Bachelor’s degree in Computer Science, Machine Learning, or a related discipline.
• 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.
• Extensive programming experience in Python and C++.
• Hands-on experience with PyTorch.
• 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.

Nice To Haves

• Programming experience with Swift.
• 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).

Responsibilities

• Train, evaluate, and deploy purpose-built vision models on Apple hardware.
• Develop innovative techniques to optimize model performance, efficiency, and scalability, ensuring a seamless user experience under strict on-device constraints.
• Develop on-device software that bridges multimodal AI models and computer vision technologies with production systems deployed across Apple devices.
• Optimize on-device inference latency, memory footprint, and computational efficiency of CV/ML models.
• Benchmark, profile, and evaluate the power consumption and thermal performance of models running on Apple silicon.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior