Machine Learning Engineer, Video Engineering

Help define the next generation of photo and video experiences at Apple. The Video Engineering group develops key image and video technologies that contribute to experiences across many Apple products and services. As a Machine Learning Engineer, you'll be developing breakthrough ML models that power spatial media features, including 3D photos, immersive video, and scene reconstruction, reaching hundreds of millions of users. As a member of a fast-paced team, you will have the unique and exciting opportunity to shape upcoming products at the frontier of generative AI, computer vision, and 3D understanding, with a strong emphasis on taking ideas from research to production.

This role requires an independent, self-motivated, and creative engineer with deep expertise in machine learning, coupled with a strong understanding of 3D computer vision and computer graphics. Your primary focus will be applying cutting-edge machine learning techniques to complex 3D visual challenges to create customer impact across current and future Apple products.

Bachelor's degree in Computer Science, Electrical/Computer Engineering, or a related field.\n3+ years of experience developing and shipping machine learning models, with a focus on computer vision or generative AI.\nExpert-level proficiency in Python and PyTorch or equivalent ML frameworks.\nStrong experience with diffusion models for image synthesis, video generation, 3D generation, or related domains.\nSolid understanding of 3D computer vision including depth estimation, multi-view geometry, 3D reconstruction, novel view synthesis, or neural scene representations.\nWorking knowledge of 3D computer graphics concepts such as rendering, camera models, scene representations, and coordinate systems.\nWorking knowledge of C++ for performance-critical components.\nAbility to leverage AI coding assistants and LLM-based tools to accelerate development, prototyping, and problem-solving workflows.

MS or PhD in Computer Science, Machine Learning, Computer Vision, or a related field.\nPublications in top-tier ML or vision venues.\nExperience with video diffusion models, 3D Gaussian Splatting, neural radiance fields, or differentiable rendering.\nExperience with distributed training at scale.\nFamiliarity with on-device ML deployment.\nTrack record of shipping ML-powered features in consumer products.\nGood written and oral interpersonal skills.