Machine Learning Systems Engineer - Video Computer Vision

Sunnyvale, California, United States Machine Learning and AI

The incredible potential of multimodal foundation models and large language models has unlocked machine learning applications that were previously thought infeasible. 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/Face Kit, 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.
• Engage with cross‑functional teams to understand and influence requirements, brainstorm the solution space, and propose, design and implement debuggable and maintainable Computer Vision systems meeting requirements.
• Design experiments and evaluations to understand quality and on‑device deployment tradeoffs, driving informed system design decisions.
• Debug concurrent systems on embedded devices via a variety of existing tools and techniques; develop innovative debug tools and visualizations when existing ones don't fit the bill.

• Bachelor’s degree in Computer Science, Machine Learning, or a related discipline, and 3+ years of relevant industry experience.
• Proven track record of writing high‑quality production code for shipped on‑device CV/ML features deployed on embedded platforms
• 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, Core Foundation, and Reality Kit 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).

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $150,400 and $277,600, and your base pay will depend on your skills, qualifications, experience, and location.

Apple employees also have the opportunity to become an Apple shareholder through participation in…