Apple - Sunnyvale, CA
posted 4 months ago
Apple's Video Computer Vision (VCV) Face and Body technologies team is seeking a talented Machine Learning Data Pipeline Software Engineer to join our innovative group. In this role, you will be instrumental in developing algorithms that enhance the Apple Vision Pro's Eyesight, Persona, and other VisionOS technologies. You will collaborate with a dynamic team of Computer Vision and Deep Learning researchers and engineers, tackling previously unsolved challenges and advancing the state of the art in Computer Vision, Machine Learning, 3D Reconstruction, and Neural Rendering algorithms. Your contributions will significantly impact how users experience the world through spatial computing applications. As a Machine Learning Data Pipeline Software Engineer, you will focus on creating and optimizing automated data processing pipelines at scale. You will work closely with Infrastructure and Machine Learning Engineers to develop solutions for complex problems related to 3D reconstruction, synthetic data generation, and photogrammetry. This position involves extensive research and development, where you will design, implement, benchmark, and distribute large-scale datasets for ambitious computer graphics and computer vision projects. Your work will be crucial in ensuring the delivery of high-quality software that meets the needs of end-users, while also pushing the boundaries of what is possible in the field of computer vision. The ideal candidate will have a strong background in pipeline development, particularly in contexts such as synthetic data, feature films, games, or visual effects (VFX). You should possess a deep understanding of data structures and algorithms, along with a passion for delivering high-quality software solutions. Excellent communication skills and the ability to work effectively within cross-functional teams are essential for success in this role. If you are self-motivated and thrive in a fast-paced environment, we encourage you to apply and be part of our extraordinary team.