Machine Learning Engineer

Apple · Operating Systems · Laptops · Bachelor's Degree · Python · C++ · 2 days ago

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In office (Cupertino)

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Confirmed on the employer's own hiring board on Nov 7, 2026. First seen by Alion on Nov 5, 2026. Apple scores A on the Alion truth index.

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Apple

Apple is an American multinational technology company founded in 1976 by Steve Jobs, Steve Wozniak and Ronald Wayne, and headquartered in Cupertino, California. It designs and sells consumer hardware including the iPhone, Mac, iPad, Apple Watch, AirPods and Vision Pro, together with the operating systems and silicon that run them. A growing services division built around the App Store, iCloud, Apple Music, Apple TV+ and Apple Pay now contributes a large share of profit, making Apple one of the most valuable companies in the world.

apple.com · HQ: Cupertino, United States · Smartwatches & Fitness Trackers · Operating Systems · Tablets · Laptops · Smartphones · 5000+ employees · Est. 1976

Tech stack of Apple

At Apple, we are constantly pushing the boundaries of what is possible, driven by our belief in the transformative power of new ideas. We are seeking a highly motivated and talented machine learning engineer to join our All-Scale Modeling team. You will work at the forefront of development, contributing to the creation of differentiating technologies for products that will delight and inspire millions of Apple customers.

Description

Develop end-to-end ML systems to solve complex physics modeling problems for Apple hardware development and innovation.

Optimize kernels for performance and efficiency.

Design and implement advanced agentic system for complex tasks.

Document and share findings to influence roadmap decisions.

Opportunities to collaborate with world-class teams.

Minimum Qualifications

Strong ML background in algorithms and engineering.

Proficiency in Python/C++ development.

Strong analytical and problem-solving skills.

Rich experience in deploying, experimenting, and benchmarking models.

B.S., M.S., or Ph.D. degree in Computer Science, Electrical Engineering, or a related field.

Preferred Qualifications

Proficiency in CUDA or Metal programming.

Strong background in numerical methods and physics (ME, EM, CFD, etc).

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