Staff Generative AI Research Engineer, Reasoning & Memory - SIML

Apple Inc

Quick summary

Work type: On-site
Location: Cupertino, CA
Salary: $181,100–$318,400 / yr
Posted: 63 days ago
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $221k

This role $250k

$163k most similar roles pay here $335k

This role pays more than 78% of similar roles. Most pay $191,406–$249,750 — the shaded band above. At the midpoint, this role pays about $250k 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 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 · Staff Generative AI Research Engineer, Reasoning & Memory - SIML

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As a Staff Generative AI Research Engineer at Apple’s System Intelligence and Machine Learning (SIML) Content Understanding team, you will collaborate on projects aimed at advancing Apple Intelligence capabilities by developing algorithms for agentic reasoning and memory systems. Your daily tasks include optimizing prompts and post-training techniques, leveraging reinforcement learning and multimodal reasoning to enhance system-wide embeddings and personalized RAG workstreams. You will also contribute to the evaluation of these innovations through automatic assessment methods while interfacing with large-scale modeling infrastructure. The ideal candidate possesses a PhD or MSc in Computer Science or related fields, expertise in machine learning fundamentals, proficiency in PyTorch, and experience with multimodal training and distributed systems. This role involves working closely with hardware engineers to integrate cutting-edge algorithmic innovations into emerging agentic experiences at Apple.

Skills

Python PyTorch Reinforcement Learning Multimodal Training Pre-training Post-training Distributed Training Large-Scale Data Infrastructure CI/CD

What you'll do

Develop advanced algorithms for agentic reasoning and memory systems.
Optimize prompts and refine post-training processes for generative models.
Apply reinforcement learning techniques to enhance system capabilities.
Collaborate on multimodal reasoning projects to integrate diverse data types.
Evaluate automatic evaluation approaches for agentic workflow effectiveness.

What we're looking for

PhD or MSc in Computer Science/Electrical Engineering with a focus on machine learning.
Strong expertise in reinforcement learning, multimodal reasoning, or pre/post-training models.
Proficiency in ML toolkits such as PyTorch and experience with automatic evaluation approaches.
Proven research contributions through publications in top-tier conferences or open source projects.
Experience with building and deploying multimodal large language models.

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