GPU ML Engineer

Apple Inc

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Quick summary

Work type: On-site
Location: Cupertino, CA
Salary: $150,400–$277,600 / yr
Posted: 96 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

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Competitive pay

How this pay compares to similar roles

Similar $224k

This role $214k

$135k $293k

below market most similar roles pay here above market

This role pays more than 54% of similar roles. Most pay $196,750–$251,150 — the blue band above. At the midpoint, this role pays about $214k versus about $224k for comparable roles.

Based on 240 similar postings.

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About Apple Inc

Apple Inc. is a multinational technology company known for designing and manufacturing consumer electronics, software, and online services, including the iPhone, Mac, iPad, and App Store. Industry: Consumer Electronics & Software

Apple Inc currently has 3497 open roles on FindRole.

Listed pay typically runs $174,149–$277,600 across 2702 roles with salary data.

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At a glance

TL;DR · GPU ML Engineer

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The GPU ML Engineer joins the Compute Frameworks team within the GPU, Graphics and Displays organization. This role focuses on providing high-performance data parallel algorithms for iOS, macOS, and Apple TV, specifically targeting linear algebra, image processing, and machine learning. The engineer will add optimized GPU compute kernels, define and implement APIs in Metal Performance Shaders, and perform in-depth compiler and kernel level optimizations. Key responsibilities include tuning GPU-accelerated compute across products and partnering with Platform Architecture teams to define the hardware roadmap for future silicon. Candidates must possess experience in GPU compute kernel framework development, system level programming, computer architecture, and high performance parallel programming. The work requires a strong understanding of machine learning fundamentals, mathematics, and numerical methods to accelerate networks on Apple Silicon.

Skills

Metal Performance Shaders GPU Programming Machine Learning Computer Vision Linear Algebra Parallel Programming Computer Architecture Numerical Methods

What you'll do

Develop optimized GPU compute kernels for machine learning, image processing, and linear algebra.
Define and implement APIs within the Metal Performance Shaders framework.
Perform compiler and kernel-level optimizations to maximize performance across various hardware families.
Partner with architecture teams to define the GPU compute hardware roadmap.
Analyze performance metrics on future silicon to inform hardware development.
Tune GPU-accelerated compute performance across all Apple products.

What we're looking for

Technical BS/MS degree or equivalent experience.
2 plus years of experience.
Experience in GPU compute kernel framework development, maintenance, and optimization.
Experience with system level programming and computer architecture.
Experience with high performance parallel programming and GPU programming.
Excellent programming, problem-solving, communication, and collaboration skills (preferred).
Good understanding of machine learning fundamentals (preferred).
Background in mathematics, including linear algebra and numerical methods (preferred).

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