Distinguished Engineer, AI Infrastructure

Apple Inc

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Quick summary

Work type: On-site
Location: Cupertino, CA
Salary: $311,100–$496,900 / yr
Posted: 20 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $221k

This role $404k

$126k $537k

below market most similar roles pay here above market

This role pays more than 96% of similar roles. Most pay $174,600–$267,243 — the blue band above. At the midpoint, this role pays about $404k versus about $221k 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 · Distinguished Engineer, AI Infrastructure

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As a Distinguished Engineer, AI Infrastructure within the Machine Learning Platform Technologies - ML Compute organization, you will provide technical leadership to build and evolve next-generation AI infrastructure. You will shape the architecture and long-term technical strategy for large-scale training and inference systems across a multi-cloud heterogeneous compute fleet. Your daily responsibilities include designing distributed systems for job scheduling, cluster management, and cost governance while optimizing end-to-end performance for frontier and production models. You will utilize backend languages such as Python, C++, Go, or Rust, alongside cloud-native architectures like Kubernetes. The role requires expertise in ML accelerators like GPUs and TPUs, as well as deep learning frameworks including PyTorch and JAX, to solve complex problems at the intersection of AI research, systems, and cloud infrastructure.

What does a Engineer earn in California?

Median $199500 from 103 postings across 31 companies.

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Skills

Distributed Systems Python C++ Go Rust Kubernetes PyTorch JAX Cloud-Native Architecture Performance Profiling Distributed Training Inference Systems

What you'll do

Define the technical vision and roadmap for frontier AI infrastructure across a multi-cloud heterogeneous compute fleet.
Design and build distributed systems for job scheduling, cluster management, and cost governance.
Optimize end-to-end performance of AI training and inference workloads in partnership with ML researchers.
Shape the architecture and long-term technical strategy for large-scale training and inference systems.
Influence how frontier and production models are trained, deployed, and scaled across diverse accelerator platforms.
Mentor senior engineers and set long-term architectural vision across multiple organizations.

What we're looking for

Bachelor’s degree in Computer Science, a relevant technical field, or equivalent practical experience.
15 years of experience designing and building very large-scale distributed systems.
Proficiency in at least one backend language such as Python, C++, Go, or Rust.
Proficiency in cloud-native architectures and compute orchestration platforms like Kubernetes.
Hands-on experience working with ML accelerators such as GPUs and TPUs.
Track record of mentoring senior engineers and setting long-term architectural vision across organizations.
Master’s degree or PhD in Computer Science or related technical fields (preferred).
Experience in running distributed training and/or inference workloads in production (preferred).

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