Machine Learning Engineer, Apple Services Engineering

Apple Inc

Quick summary

Work type
On-site
Location
Seattle, WA
Salary
$171,600–$302,200 / yr
Posted
24 days ago

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $224k
This role $237k
$156k most similar roles pay here $318k

This role pays more than 64% of similar roles. Most pay $198,800–$249,750 — the shaded band above. At the midpoint, this role pays about $237k versus about $224k for comparable roles.

Based on 240 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 1723 open roles on FindRole.

Listed pay typically runs $162,500–$272,100 across 1398 roles with salary data.

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At a glance

TL;DR · Machine Learning Engineer, Apple Services Engineering

Join Apple Services Engineering as a senior Machine Learning Engineer and help design, build, and deploy machine learning pipelines that personalize the App Store for billions of users worldwide. You will work closely with ML researchers to transition prototype models into highly optimized production systems, ensuring low latency and high throughput across various media offerings like App Store, Apple TV, and more. Your responsibilities include implementing robust monitoring and A/B testing infrastructure while maintaining a strong focus on engineering best practices and code quality. Ideal candidates possess extensive experience in Python AI/ML tech stack including PyTorch, scikit-learn, and big data technologies such as Spark and Hadoop. This role offers the unique opportunity to work on large-scale personalized recommender systems for apps, games, videos, podcasts, and fitness content, impacting billions of Apple users globally.

What you'll do

  • Design and maintain scalable machine learning pipelines for personalization models.
  • Transition prototype models into production-ready systems with ML researchers.
  • Optimize model inference to ensure low latency and high throughput globally.
  • Implement monitoring and A/B testing frameworks to evaluate model performance.
  • Ensure robustness of production systems through rigorous evaluation and testing.

What we're looking for

  • 7+ years of relevant work experience in software engineering and machine learning.
  • Strong background in building, scaling, and deploying large-scale ML models and recommendation systems.
  • Proficiency with Python AI/ML tech stack including PyTorch, scikit-learn, numpy, scipy, pandas.
  • Solid understanding of machine learning algorithms, deep learning, and generative AI techniques.
  • Experience with big data technologies such as Spark, Hadoop, Kafka for data processing pipelines.
  • Expertise in ML infrastructure, model optimization, and serving models at scale with low latency.
  • Strong written and oral communication skills with a collaborative mindset.

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