Research Manager, Multimodal Reasoning

Apple Inc

Confirmed live yesterday Trusted

Quick summary

Work type
On-site
Location
Cupertino, CA
Salary
$237,600–$356,400 / yr
Posted
42 days ago
Freshness
Confirmed live yesterday
Nearby
99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $247k
This role $297k
$164k most similar roles pay here $377k

This role pays more than 82% of similar roles. Most pay $213,687–$281,300 — the shaded band above. At the midpoint, this role pays about $297k versus about $247k 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 1984 open roles on FindRole.

Listed pay typically runs $175,000–$277,600 across 1590 roles with salary data.

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At a glance

TL;DR · Research Manager, Multimodal Reasoning

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Research Manager, Multimodal Reasoning - SIML is a senior role within the System Intelligence and Machine Learning Content Understanding team. The manager will lead cross-functional teams to advance Apple Intelligence capabilities by focusing on multimodal reasoning and emerging agentic experiences. Daily responsibilities include setting up forward-looking research investigations, developing algorithms, and prototyping innovations in collaboration with system engineers. The role requires expertise in state-of-the-art LLM workflows, including prompt optimization, post-training, alignment, automatic evaluation, distributed training, and inference. Candidates must possess strong fundamentals in machine learning and generative modeling, specifically regarding reinforcement learning or multimodal training. Technical requirements include proficiency with PyTorch and experience with large-scale data infrastructure. The work involves solving complex problems related to system-wide embeddings, personalized RAG workstreams, tool calling, context compaction, and memory systems.

Skills

LLM Multimodal Reasoning Generative Modeling PyTorch Reinforcement Learning RAG Distributed Training Prompt Optimization Post-training Alignment Large-scale Data Infrastructure Machine Learning Algorithm Development

What you'll do

  • Lead and grow high-performing machine learning teams of individual contributors.
  • Develop advanced algorithms for multimodal reasoning and generative modeling.
  • Manage research workstreams involving system-wide embeddings, personalized RAG, and tool calling.
  • Implement state-of-the-art LLM workflows including prompt optimization, post-training, and alignment.
  • Prototype and integrate bleeding-edge algorithmic innovations into agentic experiences.
  • Transition applied research initiatives into customer-facing products and features.
  • Manage large-scale modeling and data infrastructure for distributed training and inference.

What we're looking for

  • PhD or MSc in Computer Science, Electrical Engineering, Mathematics, Physics, or a related field with a focus on machine learning.
  • Strong fundamentals in Machine Learning and Generative Modeling.
  • 3+ years of experience leading and growing high-performing machine learning teams of individual contributors.
  • Expertise in Reinforcement Learning, Multimodal Training, or Pre-training/Post-training foundation models.
  • Proficiency in using ML toolkits such as PyTorch.
  • Proven track record of research contributions through publications in top-tier conferences or open source contributions to algorithms.
  • Experience leading applied research efforts in Multimodal-LLMs and transitioning initiatives into customer-facing experiences.
  • Familiarity with distributed training and large-scale data infrastructure.

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