Machine Learning Engineer

Apple Inc

Quick summary

Work type
On-site
Location
San Diego, CA
Salary
$139,500–$258,100 / yr
Posted
62 days ago

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.

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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, creatively addressing data limitations, and applying new tools to multi-modal sensor fusion challenges in health and wellness. The engineer will be responsible for developing and validating ML-driven algorithms across the full lifecycle, including data strategy, modeling, evaluation, optimization, and deployment. Key tasks include prototyping with real and synthetic data, designing experiments to quantify performance, optimizing algorithms for on-device constraints, and collaborating cross-functionally with various teams to integrate algorithms into products. The ideal candidate has a strong background in machine learning, signal processing, and experience with modern AI techniques such as generative and agentic AI, along with proficiency in Python and the ability to work effectively with incomplete or noisy datasets.

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 enhance development speed.
  • Design experiments and evaluation methods to measure performance and refine algorithms accordingly.
  • Optimize algorithms for robustness, efficiency, and deployment on devices with strict constraints.
  • Collaborate cross-functionally with various teams to integrate algorithms into final products.
  • Analyze failure modes and quantify trade-offs to drive data-driven improvements in algorithms.

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 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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