Machine Learning Research Engineer, LLM

Apple Inc

Quick summary

Work type: On-site
Location: Seattle, WA
Salary: $139,500–$258,100 / yr
Posted: 2 days ago
Nearby: 99+ roles within 25 mi

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $221k

This role $199k

$125k most similar roles pay here $277k

This role pays less than 63% of similar roles. Most pay $192,250–$249,750 — the shaded band above. At the midpoint, this role pays about $199k versus about $221k 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 1798 open roles on FindRole.

Listed pay typically runs $162,500–$272,100 across 1459 roles with salary data.

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At a glance

TL;DR · Machine Learning Research Engineer, LLM

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Apple is seeking a Machine Learning Research Engineer to join its Foundation Model Preparation and Algorithm Team at various seniority levels, aiming to integrate cutting-edge AI research into Apple products. This role involves building advanced AI infrastructure and algorithms that optimize large language models (LLMs) for both on-device and server-based applications, directly impacting billions of users. The ideal candidate will have a strong background in developing state-of-the-art LLMs and experience with Python, C/C++, and general system administration. Key responsibilities include creating reliable model optimization pipelines, implementing advanced post-training techniques, and collaborating with experts in ML tools, datasets, and evaluation to drive scientific investigations and overcome technical challenges in the neural network lifecycle.

Skills

Python C/C++ LLM LoRA fine-tuning neural network optimization quantization palettization LLM pre-training post-training on-device/server scale deployment infrastructure management debugging experimental rigor CI/CD

What you'll do

Develop state-of-the-art optimization pipelines for Apple Foundation models.
Design and implement advanced post-training techniques for AI models.
Collaborate on the creation of scalable ML infrastructure and tools.
Conduct rigorous experiments to benchmark LLM optimization algorithms.
Fine-tune large language models using LoRA and other methods.
Optimize neural networks through quantization, palettization, and more.

What we're looking for

Experience developing, optimizing, or training large language models (LLMs).
Proficient in Python and general system administration for infrastructure management.
Applied research background in neural network model lifecycle and training.
Track record of conducting scientific investigations and experiments in AI/ML.
BS degree with 3+ years of relevant experience in ML engineering or science.
Experience with LLM LoRA fine-tuning, quantization, and palettization techniques.

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