Principal Applied Research Engineer/Scientist

Apple Inc

Quick summary

Work type
On-site
Location
Cupertino, CA
Salary
$212,000–$386,300 / yr
Posted
88 days ago
Nearby
99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $205k
This role $299k
$133k most similar roles pay here $413k

This role pays more than 94% of similar roles. Most pay $161,000–$249,750 — the shaded band above. At the midpoint, this role pays about $299k versus about $205k 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.

Most-posted roles

View all roles at Apple Inc

At a glance

TL;DR · Principal Applied Research Engineer/Scientist

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As a Principal Applied Research Engineer at Apple, you will join a pioneering team focused on advancing self-improving systems, agentic memory frameworks, and personalized autonomous multi-agent systems. Your daily work involves designing intelligent architectures that continuously learn from real-world data, retain contextual knowledge, and coordinate across agents to solve complex user problems. You will lead research initiatives, develop scalable ML systems, and collaborate with cross-functional teams to integrate cutting-edge AI technologies into Apple’s hardware and software ecosystem. The role requires deep expertise in transformer-based large language models (LLMs) and multi-modal foundation models, hands-on experience throughout the model lifecycle, and a strong background in computer science or machine learning. This position offers an unparalleled opportunity to influence high-level architecture decisions and drive innovative solutions that enhance user experiences at scale.

Skills

Python PyTorch TensorFlow Transformer LLMs Multi-modal_models Cross-modal_attention CI/CD MLOps AWS Kubernetes Docker Git Scikit-learn PostgreSQL Redis NVIDIA_GPU CUDA AutoML Ray

What you'll do

  • Advance self-improving systems that learn from real-world data and adapt autonomously.
  • Design agentic memory frameworks enabling long-term reasoning and contextual continuity.
  • Architect multi-agent systems for personalized, coordinated problem-solving in complex environments.
  • Lead rapid prototyping to translate research into scalable, validated user experiences.
  • Influence platform strategy by integrating ML systems across hardware, software, and services.

What we're looking for

  • MSc or PhD in Computer Science, Machine Learning, or related field.
  • Deep expertise in transformer-based LLMs and multi-modal foundation models.
  • Hands-on experience across the full model lifecycle from pre-training to optimization.
  • Expertise in designing AI agents for complex reasoning under compute constraints.
  • Ability to influence high-level architecture decisions and advocate for research directions.

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