Senior machine learning platform engineer, Evaluation & Privacy

Apple Inc

Quick summary

Work type
On-site
Location
Cupertino, CA
Salary
$181,100–$318,400 / yr
Posted
1 day ago

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $212k
This role $250k
$154k most similar roles pay here $336k

This role pays more than 82% of similar roles. Most pay $178,689–$246,150 — the shaded band above. At the midpoint, this role pays about $250k versus about $212k 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 machine learning platform engineer, Evaluation & Privacy

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As a Senior Machine Learning Platform Engineer at Apple’s Evaluation & Privacy team, you will collaborate with engineers and scientists across various products to integrate their machine learning initiatives onto the company's privacy-preserving platform. Your daily tasks include designing systems that facilitate the transition of research prototypes into production-ready solutions for privacy-preserving ML training and evaluation, scaling distributed infrastructure to support a growing portfolio of teams, and partnering with product teams to ensure they meet Apple’s stringent privacy standards. This role requires expertise in Python or Swift, proficiency in building background software on autonomous systems like iPhones, and experience with large-scale distributed systems. Ideal candidates are passionate about customer privacy and have experience with technologies such as differential privacy and private federated learning.

Skills

Python Swift Docker Kubernetes Terraform AWS CI/CD PostgreSQL Redis Git Differential Privacy Secure Multi-Party Computation Private Federated Learning PII Redaction Frameworks

What you'll do

  • Design and build privacy-preserving ML platforms for large-scale distributed training and evaluation.
  • Operate systems that support private federated learning across millions of user devices.
  • Partner with applied scientists to develop production-grade privacy-preserving algorithms.
  • Scale infrastructure to accommodate growing teams and products requiring privacy-preserving ML.
  • Collaborate on adopting the platform by product teams, ensuring adherence to Apple's privacy standards.

What we're looking for

  • At least 2 years of industry experience with a Bachelor’s degree in Computer Science or related field.
  • Proficient in Python and/or Swift for software development.
  • Experience designing and operating large-scale distributed systems.
  • Strong background in building autonomous system software like iPhone background processes.
  • Ability to collaborate effectively across diverse technical teams and adapt to new challenges.

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