Job Details

Job Information

Machine Learning Software Engineer for Location and Spatial Awareness , Sensing & Connectivity
AWM-9576-Machine Learning Software Engineer for Location and Spatial Awareness , Sensing & Connectivity
4/8/2026
4/13/2026
Negotiable
Permanent

Other Information

www.apple.com
Cupertino, CA, 95015, USA
Cupertino
California
United States
95015

Job Description

No Video Available
 

Weekly Hours: 40

Role Number: 200656105-0836

Summary

Help craft the next generation of spatial awareness and applied perception technologies at Apple. Our team focuses on innovating, building, and productizing new ways for our devices to understand and interact with the physical world and the user. We leverage cutting-edge computer vision, foundation models, and machine learning to enable highly intuitive, seamless forms of human-computer interaction.

Description

Join a team that designs, implements, and powers brand new technologies and services on a platform that empowers millions of developers and reaches over a billion users. We are looking for a highly motivated and creative Software Engineer with a strong background in Machine Learning and Computer Science to help develop new technologies for special projects on the Location Services team. Our special projects target innovative new signals, sensors, and algorithms to enhance location-aware user experiences.

In this role, you will architect and implement production software systems for new ML technologies, fusing them with existing location and spatial capabilities to bring new experiences to our users. You will collaborate with developers on other iOS teams to architect full-stack iOS solutions. By designing and implementing technologies that integrate machine learning with wireless and spatial sensors, you will help solve real-world problems and participate in brainstorming the future of iOS.

Minimum Qualifications

  • Ph.D. (or M.S. with equivalent applied research experience) in Computer Engineering, Computer Science, Electrical Engineering, or a related field.

  • Deep expertise in Machine Learning and Computer Vision, with a strong focus on Vision Transformers (ViTs), CNNs, and Foundation Models.

  • Proven track record of developing and optimizing efficient ML training pipelines, specifically utilizing Active Learning, domain adaptation, or semi-supervised learning to reduce data annotation bottlenecks.

  • Hands-on experience with egocentric video understanding, action recognition, or scene classification.

  • Strong programming skills in Python and C/C++, with deep proficiency in modern deep learning frameworks (PyTorch, TensorFlow).

  • Experience working with novel or multi-modal sensor data (e.g., polarization, depth, IR) and synthetic/semi-synthetic data generation.

  • Ability to optimize data-loading and training infrastructure to maximize GPU efficiency.

  • Familiarity with 3D computer vision and spatial/robotic perception.

Preferred Qualifications

  • Takes initiative to address new problems and responsibility for the results

  • Excellent collaboration skills and a proven ability to publish in top-tier ML/CV conferences or journals

  • Interested in creating new technologies and user experiences.

  • Passion for actively learning new skills, techniques, and programming languages/libraries/frameworks.

  • Thrives in a collaborative environment and communicates effectively.

  • Creative and inquisitive, seeking to solve everyday problems in innovative ways.

  • Laser-focused on the smallest details that are meaningful to our customers.

  • Desire to be exposed to all aspects of development: prototyping, planning, designing, productizing, launching, and scaling.

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant (https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf) .

Other Details

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