Machine Learning Engineer

Apple Inc

Quick summary

Work type
On-site
Location
Cupertino, CA
Salary
$147,400–$272,100 / yr
Posted
54 days ago

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $217k
This role $210k
$132k most similar roles pay here $287k

This role pays less than 53% of similar roles. Most pay $184,050–$249,750 — the shaded band above. At the midpoint, this role pays about $210k versus about $217k 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’s Health Sensing team is hiring a Machine Learning Engineer to develop advanced health algorithms that integrate classical machine learning and signal processing with generative AI techniques. This role involves moving quickly from idea to prototype, overcoming data limitations, and applying new tools to multi-modal sensor fusion problems in health and wellness. The engineer will work across the entire algorithm lifecycle, including data strategy, modeling, evaluation, optimization, and deployment, collaborating closely with user studies, hardware, software, and product teams. Key responsibilities include developing and validating ML algorithms for health applications, designing experiments to quantify performance, optimizing algorithms for on-device deployment, and analyzing failure modes to drive improvements. The ideal candidate has a strong background in machine learning, signal processing, and applied mathematics, proficiency in Python, and experience with modern AI techniques such as generative AI.

What you'll do

  • Develop and validate machine learning algorithms for health applications throughout the product lifecycle.
  • Prototype multiple algorithmic approaches using real and synthetic data to speed up development.
  • Design experiments and evaluation methods to measure performance and guide improvements.
  • Optimize algorithms for efficiency, robustness, and deployment on devices with constraints.
  • Collaborate cross-functionally with teams to integrate algorithms into products.
  • Analyze failure modes and tradeoffs to drive algorithmic enhancements based on data.

What we're looking for

  • Bachelor’s degree in a relevant technical field or equivalent industry experience.
  • Strong foundation in machine learning, statistics, signal processing, and applied mathematics.
  • Experience applying modern AI techniques like generative AI for algorithm development.
  • Proficiency in Python for rapid prototyping and iterative improvement of algorithms.
  • Ability to own the full lifecycle of algorithm development from exploration to integration.
  • Familiarity with on-device ML frameworks and optimization under resource constraints.

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