3D Computer Vision Research Engineer, Apple Maps

Apple is where individual imaginations come together to create products, services, and experiences that enrich people's lives. At Apple, great ideas become stronger through collaboration, diverse perspectives, and a shared commitment to doing our best work. Here, you will do more than join a team - you will add something meaningful.

The 3D Vision team at Apple Maps is looking for exceptional computer vision and machine learning talent to help build the next generation of map automation and spatial intelligence technologies. Our team researches, develops, and deploys algorithms at global scale, working with extremely large multimodal datasets collected from aerial, satellite, and ground-based platforms.

As part of this team, you will work on challenging real-world problems in visual understanding, map feature extraction, scene understanding, and physical-world reasoning. The technologies we build help create and maintain high-quality map data that powers user-facing Apple Maps experiences and broader Apple products.

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.

Responsibilities:

Prototype, develop, and evaluate computer vision and machine learning algorithms for real-world map feature extraction problems.

Build models and systems for visual understanding, scene understanding, map automation, and physical-world reasoning.

Work with large multimodal datasets, including aerial, satellite, and ground imagery.

Develop methods for detecting, extracting, classifying, and validating map-relevant features from imagery and sensor data.

Collaborate with cross-functional teams to bring research ideas into production-quality systems.

* Tackle open-ended technical challenges with curiosity, pragmatism, and strong engineering judgment.

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.

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.