Machine Learning Tools Engineer, SIML

Apple Inc

Quick summary

Work type
On-site
Location
Cupertino, CA
Salary
$147,400–$220,900 / yr
Posted
38 days ago

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $214k
This role $184k
$134k most similar roles pay here $272k

This role pays less than 72% of similar roles. Most pay $178,614–$249,750 — the shaded band above. At the midpoint, this role pays about $184k versus about $214k 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 969 open roles on FindRole.

Listed pay typically runs $163,300–$272,100 across 756 roles with salary data.

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At a glance

TL;DR · Machine Learning Tools Engineer, SIML

Join the Intelligence System Experience (ISE) team at Apple as a Machine Learning Tools Engineer and help build the foundational tools that enable groundbreaking generative modeling technologies. This hands-on role involves designing and maintaining core ML infrastructure, including training pipelines, experiment tracking systems, and deployment tooling, to enhance productivity and reliability for researchers and engineers. You will develop Python-based SDKs, CLIs, and APIs to simplify interactions with compute resources and models, ensuring robustness, performance, and user-friendliness. Collaborating closely with MLOps and platform teams, you will support the seamless integration of end-to-end systems while addressing the needs of a large and growing user base. Strong in Python, familiar with ML frameworks like PyTorch or TensorFlow, and experienced with Linux and version control, you will thrive in this multidisciplinary environment focused on innovative system experiences.

What you'll do

  • Design and maintain core machine learning infrastructure components like training pipelines and deployment tooling.
  • Develop Python-based SDKs and CLIs that simplify interactions with compute resources for ML engineers.
  • Collaborate with researchers to identify and solve pain points in model development processes.
  • Ensure tools are robust, performant, and user-friendly with comprehensive documentation.
  • Partner with MLOps teams to integrate end-to-end systems and support scaling efforts.

What we're looking for

  • 3+ years of software development experience with strong Python proficiency
  • Familiarity with machine learning fundamentals and frameworks like PyTorch, TensorFlow, JAX
  • Experience working with Linux systems, containers (Docker), and version control (Git)
  • Strong debugging, analytical, and problem-solving skills
  • Ability to collaborate across teams with competing timelines and technical constraints
  • Prior experience in ML platform, infrastructure, or productivity tools development
  • Exposure to distributed training, experiment tracking, or model serving infrastructure

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