On-Device ML Infrastructure Engineer, ML User Experience, APIs & Integration, Graphics, Games and Machine Learning

Apple Inc

Quick summary

Work type: On-site
Location: Cupertino, CA
Salary: $147,400–$272,100 / yr
Posted: 56 days ago
Nearby: 99+ roles within 25 mi

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $222k

This role $210k

$132k most similar roles pay here $287k

This role pays less than 52% of similar roles. Most pay $194,000–$249,325 — the shaded band above. At the midpoint, this role pays about $210k versus about $222k for comparable roles.

Based on 239 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 · On-Device ML Infrastructure Engineer, ML User Experience, APIs & Integration, Graphics, Games and Machine Learning

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As an On-Device ML Infrastructure Engineer at Apple, you will join a dynamic team focused on developing the end-to-end developer experience for machine learning on Apple devices. Your primary responsibilities include creating and refining APIs that enable efficient model authoring and conversion for Apple platforms, integrating these tools into both internal and external repositories to showcase their capabilities, and designing optimizations across various levels of the ML pipeline to enhance performance. You will work with cutting-edge technologies such as PyTorch and other frameworks, requiring a strong grasp of Python programming alongside proficiency in C++. This role demands expertise in machine learning fundamentals, including model architectures and deployment optimizations like quantization, and offers the chance to significantly impact Apple’s intelligent experiences across products like Camera, Siri, and Health.

Skills

Python PyTorch C++ MLIR LLVM Quantization Pruning KV caching Hugging Face Swift GPU programming CI/CD Git JAX PostgreSQL MLOps

What you'll do

Develop APIs for efficient import and implementation of ML models in Apple’s stack.
Integrate ML tools into internal and external repositories to demonstrate peak performance.
Create optimizations across the pipeline, including source-level transformations and custom operations.
Onboard latest ML models with optimal performance to showcase authoring and runtime capabilities.
Stress test model ingestion processes to ensure efficient and high-performance integration.