Description
You will join a small, fast-paced team of computer vision and machine learning experts working on large-scale visual understanding for Apple Maps. This role focuses on developing models and systems that extract meaningful map features from real-world imagery and other sensor data. Example areas include object and feature detection, semantic understanding, attribute prediction, imagery-based map updates, scene-level reasoning, and multimodal understanding. You will help develop novel methods that combine machine learning, 3D geometry, multimodal data, and large-scale systems to solve practical mapping problems at Apple Maps scale.
Minimum Qualifications
Strong background in computer vision and machine learning. Hands-on experience with visual understanding, object detection, segmentation, feature extraction, scene understanding, or related computer vision problems. Familiarity with 3D geometry, spatial reasoning, or large-scale geospatial data is a plus. Solid programming skills. Master’s degree with 2+ years of relevant experience.
Preferred Qualifications
PhD degree in Computer Vision, Machine Learning, AI, Computer Science, Electrical Engineering, or a related field. Publications in top-tier CV/ML conferences, such as CVPR, ICCV, ECCV, NeurIPS, ICLR, SIGGRAPH, or related venues. Experience with vision-language models, multimodal LLMs, reasoning models, or generative image/video models is a plus. Experience building ML systems for large-scale real-world visual data. Knowledge of 3D geometry, geospatial data, or computer graphics fundamentals is a plus. Strong C/C++ and Python programming skills.
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