About the role

What will you do at Apple?

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/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.

DESCRIPTION

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.

MINIMUM QUALIFICATIONS

Bachelor’s degree in Computer Science, Machine Learning, or a related

discipline, and 3+ years of relevant industry experience. Strong ML

fundamentals. 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.

PREFERRED QUALIFICATIONS

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).

Which skills does this role require?

Machine LearningComputer VisionPythonC++PyTorchMultimodal LLMsOn-device DeploymentSupervised Fine-TuningNeural Network OptimizationEmbedded SystemsModel TrainingModel EvaluationFoundation ModelsLarge Language ModelsFaceIDFaceKitGaze ControlHand Gesture ControlBody TrackingScene UnderstandingEmbedded PlatformsProduction CodeModel OptimizationScalabilityLLMs

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