Machine Learning Engineer

Apple Inc

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Quick summary

Work type: On-site
Location: Cupertino, CA
Salary: $184,700–$324,800 / yr
Posted: 80 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $225k

This role $255k

$157k $343k

below market most similar roles pay here above market

This role pays more than 84% of similar roles. Most pay $198,000–$251,400 — the blue band above. At the midpoint, this role pays about $255k versus about $225k 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 3497 open roles on FindRole.

Listed pay typically runs $174,149–$277,600 across 2702 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, you will join the Machine Learning and AI team to build the infrastructure, pipelines, systems, and models powering next-generation video technology. You will design, build, test, and scale ML systems, including training infrastructure, data ingestion and curation pipelines, and performance optimization for inference. Your daily work involves solving challenging problems across the full ML lifecycle, focusing on efficiency optimization, data handling, and production deployment. You must demonstrate proficiency in Python, C++, and PyTorch, while utilizing AI tooling like Claude. The role requires deep familiarity with ML-centric flows, computer architecture principles, and high-level design skills to create robust, modular code. You will specifically address technical problems regarding visual data, distributed training, and large-scale data pipelines to improve video experiences.

What does a Machine Learning Engineer earn in California?

Median $235750 from 200 postings across 34 companies.

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Skills

Python C++ PyTorch CUDA GPU Kernel Optimization Distributed Training Data Pipelines Inference Serving Computer Architecture Model Deployment Data Ingestion Profiling Debugging Claude

What you'll do

Design, build, and scale ML systems including training infrastructure and data ingestion pipelines.
Develop and curate data pipelines for large-scale machine learning workflows.
Optimize power and performance for ML model inference.
Develop and deploy production-ready machine learning models for video technology.
Implement custom operations in CUDA or perform low-level GPU kernel optimizations.
Manage distributed training processes and large-scale data handling.
Profile and debug ML-centric flows to ensure high throughput and robustness.
Write robust, modular, and well-tested code using Python, C++, and PyTorch.

What we're looking for

BS degree and 10+ years of hands-on industry experience building production ML systems.
Proven track record of design and implementation leadership.
Deep familiarity with ML-centric flows including training procedures, dataloaders, profiling, debugging, and model deployment.
Proficiency in Python, C++, and PyTorch.
Familiarity with computer architecture principles.
Proficiency in AI tooling and excellent high-level design skills for building robust, modular, and well-tested code.
MS specializing in ML systems, performance engineering, or a related area (preferred).
Experience with CUDA custom ops, GPU kernel optimization, distributed training, and visual data (preferred).