CVML Engineer - 3D Reconstruction

The Video Computer Vision organization is building breakthrough technologies for future Apple products. Our team delivers cutting-edge computer vision, machine learning, and graphics algorithms that power human understanding and geometric reasoning for health and fitness features. In this role, you will collaborate with world-class experts in AI, ML, Software, and Hardware to solve fundamental challenges in human-centric 3D solutions that will impact millions of users across Apple's ecosystem.

Description

We are looking for a CVML Engineer with deep expertise in multi-view geometry and modern machine learning approaches, and a genuine passion for shipping product features. You will research, adapt, and implement state-of-the-art 3D and 4D reconstruction algorithms for human understanding and geometry-driven health and fitness applications. You will design novel approaches that combine classical geometry with modern deep learning techniques to produce high-quality ground truth data for training and evaluation, as well as develop robust, high-quality runtime algorithms for on-device deployment. You will collaborate with cross-functional teams to define requirements and validation frameworks, and deliver production-ready code optimized for Apple silicon and mobile devices.

Minimum Qualifications

BS degree in Computer Vision, Machine Learning, Computer Graphics, or related fields and a minimum of 10 years relevant industry experience

Deep understanding of multi-view geometry and 3D reconstruction pipelines.

Strong proficiency in Python and PyTorch with solid software engineering practices.

Solid mathematical foundation in linear algebra, optimization, and geometry processing.

Experience with modern ML architectures and their applications to 3D problems.

Excellent communication skills and proven ability to work effectively in cross-functional teams.

Self-motivated with a track record of prioritizing effectively and delivering on schedule.

Preferred Qualifications

MS or PhD in Computer Vision, Computer Graphics, Machine Learning, Computer Science, or related fields.

Experience with human-centric 3D and 4D reconstruction approaches, datasets, and evaluation methodology.

Background in differentiable optimization and geometric deep learning approaches.

Experience optimizing ML models for mobile deployment and resource-constrained environments.

Knowledge of SLAM, bundle adjustment, and photogrammetric reconstruction techniques.

Proficiency in C/C++.