Machine Learning Engineer, Intelligent Quality Systems

Apple Inc

Confirmed live 2 days ago High trust

Quick summary

Work type
On-site
Location
Cupertino, CA
Salary
$150,400–$277,600 / yr
Posted
72 days ago
Freshness
Confirmed live 2 days ago

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $223k
This role $214k
$135k most similar roles pay here $293k

This role pays less than 51% of similar roles. Most pay $192,050–$254,750 — the shaded band above. At the midpoint, this role pays about $214k versus about $223k 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 1984 open roles on FindRole.

Listed pay typically runs $175,000–$277,600 across 1590 roles with salary data.

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At a glance

TL;DR · Machine Learning Engineer, Intelligent Quality Systems

Machine Learning Engineer - Intelligent Quality Systems joins the Intelligent Quality Systems team to build ML-powered systems that improve software quality and speed at scale. You will work across the testing lifecycle by implementing solutions for test selection, failure triage, visual validation, and coverage analysis. Your daily work involves prototyping algorithmic approaches, designing data collection and evaluation strategies, and managing large-scale test results and code change data to inform modeling decisions. The role requires expertise in machine learning fundamentals, model training, and production-quality software engineering. You will utilize technologies including LLMs, computer vision, retrieval systems, and multimodal ML to solve complex problems like change-impact prediction and automated test recommendation. This position serves as a bridge between research ideas and production reality, addressing technical risks while building robust infrastructure for large-scale software engineering environments.

What does a Machine Learning Engineer earn in California?

Median $246394 from 172 postings across 28 companies.

See salary data

What you'll do

  • Implement ML solutions for test selection, failure triage, visual validation, and coverage analysis.
  • Prototype multiple algorithmic approaches to identify the most promising directions for software quality problems.
  • Design and implement data collection, labeling, and evaluation strategies for training and measuring ML systems.
  • Analyze large-scale test results and code change data to surface patterns and inform modeling decisions.
  • Identify research-to-production gaps and technical risks in proposed machine learning solutions.
  • Build robust data platforms and infrastructure to support reliable operations across large-scale software systems.
  • Develop production-quality code for LLM-powered failure analysis, multimodal UI regression detection, and automated test recommendations.

What we're looking for

  • BS or MS in Computer Science, Machine Learning, Statistics, or a related field.
  • 3+ years of experience with machine learning in academic or professional settings.
  • Demonstrated work on substantial ML projects beyond coursework.
  • Strong programming and software engineering skills to write clean, maintainable, production-quality code.
  • Practical understanding of ML fundamentals, model training, evaluation, and debugging.
  • Ability to implement algorithms from papers or specifications.
  • Experience with NLP, large language models, code understanding, or retrieval-augmented generation (RAG).
  • Background in computer vision, multimodal ML, or building data pipelines at scale.

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