Machine Learning Systems Engineer – Video Computer Vision

Apple • Sunnyvale, CA

9h

About The Position

The Video Computer Vision (VCV) group is seeking a Machine Learning Systems Engineer to help deliver computer vision technology on Apple devices. The VCV organization develops features including FaceID/FaceKit, Gaze/Hand Gesture Control, Body Tracking, and 2D/3D Scene Understanding, balancing research and product requirements while collaborating across hardware, software, and AI teams.

As a member of the Video Computer Vision team, you will work across the stack to turn research projects into refined customer products. You will build software infrastructure that delivers multimodal context to models and optimize the software harness and models for efficient on-device deployment. In close partnership with algorithm researchers, you will also participate in post-training model alignment and evaluation.

Requirements

• Bachelor’s degree in Computer Science, Machine Learning, or a related discipline.
• At least 3 years of relevant industry experience.
• Strong machine learning fundamentals.
• A proven track record of writing high-quality production code for shipped on-device computer vision or machine learning features deployed on embedded platforms.
• Solid understanding of operating system fundamentals.
• Extensive programming experience in Python and C++.
• Hands-on experience with PyTorch.
• Familiarity with the end-to-end machine learning lifecycle, including 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.
• A robust foundational understanding of machine learning architectures, specifically Multimodal LLMs, and integrating machine learning 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, such as Apple Neural Engine or mobile GPUs.

Responsibilities

• Transform promising research projects into refined products for customers.
• Build software infrastructure to deliver multimodal context to models.
• Optimize the software harness and models for efficient on-device deployment.
• Partner with algorithm researchers on post-training model alignment and evaluation.

What This Job Offers

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