Generative AI Applied Scientist, SIML - ISE

Apple Inc

Quick summary

Work type: On-site
Location: Cupertino, CA
Salary: $147,400–$272,100 / yr
Posted: 4 days ago
Nearby: 99+ roles within 25 mi

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $207k

This role $210k

$132k most similar roles pay here $287k

This role pays less than 53% of similar roles. Most pay $167,000–$246,150 — the shaded band above. At the midpoint, this role pays about $210k versus about $207k 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 · Generative AI Applied Scientist, SIML - ISE

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Apple's System Intelligence and Machine Learning (SIML) team is seeking a senior Generative AI expert to lead the development of next-generation human-centric device interaction and multimodal scene understanding technologies. As part of this role, you will design, train, and deploy large-scale multimodal LLMs, focusing on innovative architecture and integration into production pipelines. You will collaborate with cross-functional teams to implement novel user experiences using advanced models and develop robust ML solutions that enhance system-level interactions and preferences. Essential skills include expertise in state-of-the-art transformer models, multi-modal encoders, and representation learning, along with strong Python programming abilities. This position offers the opportunity to work on cutting-edge AI technologies at scale within a dynamic research environment focused on advancing Apple's intelligent systems.

Skills

Python Transformer Models Multimodal LLMs Auto-regressive Transformers Multi-modal Encoders Representation Learning CI/CD API Development Scalable ML Models Large Language Models ML Infrastructure Software Engineering Principles

What you'll do

Design, train, and deploy large-scale multimodal LLMs throughout their lifecycle.
Implement novel user experiences using capabilities of large foundation models.
Create scalable ML models and APIs for integration into production pipelines.
Develop memory systems enabling long-term adaptation in generative AI models.
Forge collaborations with cross-functional teams to iterate on innovative solutions.

What we're looking for

PhD or Masters Degree in Computer Science, Engineering, or related field focusing on machine learning.
Strong research background with first-author publications in top-tier ML conferences.
Expert knowledge of state-of-the-art techniques in auto-regressive transformers, multi-modal encoders, and representation learning.
Experience designing, training, and deploying large-scale multimodal LLMs across the entire lifecycle.
Proficient programming skills in Python for maintaining robust machine learning codebases.

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