Senior ML Infrastructure Engineer - VE Algorithms

Apple Inc

Quick summary

Work type
On-site
Location
San Diego, CA
Salary
$139,500–$258,100 / yr
Posted
45 days ago

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $221k
This role $199k
$125k most similar roles pay here $277k

This role pays less than 64% of similar roles. Most pay $195,000–$246,150 — the shaded band above. At the midpoint, this role pays about $199k versus about $221k for comparable roles.

Based on 239 similar postings.

Employer

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 638 open roles on FindRole.

Listed pay typically runs $171,600–$272,100 across 505 roles with salary data.

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At a glance

TL;DR · Senior ML Infrastructure Engineer - VE Algorithms

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As a Senior ML Infrastructure Engineer on Apple’s Video Engineering team, you will play a pivotal role in advancing the company's photo and video features by developing cutting-edge machine learning algorithms. Your day-to-day responsibilities include optimizing training pipelines for large-scale visual pre-training across various architectures, designing workload scheduling strategies for distributed GPU clusters, profiling and optimizing the full compilation stack from high-level graph capture to target hardware, and building scalable CI/CD pipelines tailored to multi-GPU workflows. You will need advanced fluency in PyTorch, strong programming skills in Python or C++, and experience with large-scale model training. This role requires deep expertise in ML infrastructure and a focus on efficient utilization of training hardware for visual data, contributing to the development of innovative photo and video features used by millions globally.

Skills

Python PyTorch C++ Docker Kubernetes AWS CI/CD Prometheus Grafana PostgreSQL

What you'll do

  • Optimize and profile training pipelines for large-scale visual pre-training across architectures.
  • Design and implement workload scheduling strategies for distributed training on thousands of GPUs.
  • Profile and optimize the full compilation stack from high-level graph capture to target hardware.
  • Build and maintain experimentation tooling, dashboards, and scalable CI/CD pipelines for multi-GPU workflows.
  • Contribute to software projects with advanced programming skills in Python or C++.

What we're looking for

  • BS in Electrical Engineering/Computer Science or related field with at least 3 years of industry experience.
  • Extensive experience in training and adapting large language models (LLMs).
  • Advanced proficiency in PyTorch for machine learning projects.
  • Strong programming skills in Python and/or C++ with a track record of contributing to major software projects.
  • Experience in distributed training strategies for large-scale visual pre-training across various architectures.
  • Expertise in optimizing and profiling training pipelines for efficient hardware utilization.

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