Research Manager, Multimodal Reasoning

Apple Inc

Confirmed live 2 days ago Low trust

Quick summary

Work type
On-site
Location
Cupertino, CA
Salary
$237,600–$356,400 / yr
Posted
84 days ago
Freshness
Confirmed live 2 days ago
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

Role Posting Log in to save

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, system-wide embeddings, personalized RAG workstreams, tool calling, and context compaction. Day-to-day responsibilities include setting up forward-looking research investigations, developing algorithms, and prototyping bleeding-edge innovations for emerging agentic experiences in collaboration with hardware engineering and design partners. The role requires expertise in LLM workflows including prompt optimization, post-training alignment, automatic evaluation, and distributed training. Candidates must possess strong fundamentals in generative modeling and machine learning, with proficiency in PyTorch. Key technical domains include reinforcement learning, multimodal training, and pre-training foundation models, while navigating large-scale modeling and data infrastructure to transition research into customer-facing experiences.

Skills

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

What you'll do

  • Lead and grow high-performing machine learning teams of individual contributors.
  • Develop algorithms and conduct research investigations focused on multimodal reasoning.
  • Manage LLM workflows including prompt optimization, post-training alignment, and automatic evaluation.
  • Prototype and integrate bleeding-edge algorithmic innovations into agentic experiences.
  • Partner with system engineers to implement advancements in embedding systems, RAG, and tool calling.
  • 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, or a related field with a focus on machine learning.
  • Comparable professional experience in lieu of a graduate degree.
  • 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 top-tier conference publications or open source algorithm contributions.
  • Experience in leading applied research for Multimodal-LLMs and transitioning initiatives to customer-facing experiences.

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