Machine Learning Engineer

Apple Inc

Confirmed live 2 days ago High trust

Quick summary

Work type: On-site
Location: Pittsburgh, PA
Posted: 31 days ago
Freshness: Confirmed live 2 days ago
Nearby: 99+ roles within 25 mi

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Salary context

How this pay compares to similar roles

Similar $223k

$165k most similar roles pay here $276k

This listing doesn't post a salary. Most similar roles pay $192,050–$254,750.

Based on 240 similar postings.

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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

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As a Machine Learning Engineer on the Machine Intelligence Neural Design team, you will contribute to the development of impactful features by engaging in research regarding Foundation Models and Perception. You will manage the entire end-to-end machine learning pipeline, which includes creative dataset curation, model training, runtime inference integration, and on-device optimizations. Your daily work involves building production-quality inference infrastructure, developing evaluation pipelines, and creating real-time demos and visualizations of sensing data streams. To succeed, you must possess a strong foundation in LLM and multimodal models while utilizing Python, PyTorch, JAX, or TensorFlow for training. You will also develop software applications using Swift, Objective-C, C++, or Go to integrate models into the infrastructure. This role focuses on solving complex problems related to sensing systems and multimodal data including text, images, and audio.

What does a Machine Learning Engineer earn?

Median $236000 from 319 postings across 54 companies.

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Skills

Python PyTorch JAX TensorFlow Swift C++ Go Objective-C LLM Multimodal Foundation Models On-device ML Inference Infrastructure

What you'll do

Build end-to-end machine learning training and evaluation pipelines using Python and PyTorch.
Develop production-quality software to integrate ML models into Apple's software infrastructure.
Perform dataset curation and model training for foundation models and perception tasks.
Optimize machine learning models for efficient on-device inference and deployment.
Create real-time demos and visualizations of sensing data streams and model predictions.
Prototype and iterate on new ideas to deliver high-quality ML features.
Handle multimodal data including text, images, audio, and other sensor inputs.

What we're looking for

A PhD in computer science, computer engineering, or a related field is required.
A BS or MS with 3 to 5 years of ML engineering experience is an acceptable alternative to a PhD.
Strong foundation in machine learning, specifically in LLM and multimodal foundation models.
Experience building model training and evaluation pipelines in Python/PyTorch.
Experience with sensors and sensing systems.
Strong communication and presentation skills.
Proficiency in Swift, Objective-C, C++, or Go (preferred).
Experience in on-device ML model deployment and optimization (preferred).