Machine Learning Engineer

Apple Inc

Quick summary

Work type
On-site
Location
San Diego, CA
Salary
$139,500–$258,100 / yr
Posted
63 days ago
Nearby
99+ roles within 25 mi

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $217k
This role $199k
$125k most similar roles pay here $276k

This role pays less than 62% of similar roles. Most pay $184,050–$249,750 — the shaded band above. At the midpoint, this role pays about $199k 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.

Most-posted roles

View all roles at Apple Inc

At a glance

TL;DR · Machine Learning Engineer

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Apple’s Health Sensing team is hiring a Machine Learning Engineer to develop advanced health algorithms using classical ML and generative AI techniques. This role involves moving quickly from idea to product by prototyping multiple approaches, designing experiments for performance evaluation, and optimizing algorithms for on-device deployment. The engineer will collaborate with cross-functional teams including user studies, hardware, software, and product groups to integrate algorithms into products. Ideal candidates have a strong background in machine learning, signal processing, and applied mathematics, along with experience in generative AI and agentic AI. Proficiency in Python is essential, as well as the ability to work with incomplete or noisy datasets and design efficient experiments. Experience with on-device ML frameworks and distributed ML workflows is preferred.

Skills

Python Machine Learning Generative AI Agentic AI Signal Processing Statistical Validation Distributed ML Cloud-Based ML Simulation Synthetic Data Data Augmentation On-Device ML Resource-Constrained Optimization

What you'll do

  • Develop and validate health sensing algorithms using machine learning and generative AI techniques.
  • Prototype multiple algorithm approaches using real and synthetic data for rapid development.
  • Design experiments and evaluation methods to quantify performance and guide improvements.
  • Optimize algorithms for robustness, efficiency, and deployment on devices with constraints.
  • Collaborate cross-functionally to integrate developed algorithms into health products.

What we're looking for

  • Bachelor’s degree in a relevant technical field or equivalent industry experience.
  • Strong background in machine learning, statistics, signal processing, and applied mathematics.
  • Experience applying modern AI techniques including generative and agentic AI.
  • Proficiency in Python for algorithm development and optimization.
  • Ability to rapidly prototype, evaluate multiple approaches, and iterate based on results.
  • Experience owning the full lifecycle of algorithm development from exploration to integration.

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