Principal Applied Research Engineer/Scientist, Siri Labs

Apple Inc

Quick summary

Work type: On-site
Location: Cupertino, CA
Salary: $212,000–$386,300 / yr
Posted: 2 days ago
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $217k

This role $299k

$140k most similar roles pay here $413k

This role pays more than 94% of similar roles. Most pay $185,850–$248,718 — the shaded band above. At the midpoint, this role pays about $299k versus about $217k 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 1817 open roles on FindRole.

Listed pay typically runs $163,300–$272,100 across 1482 roles with salary data.

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At a glance

TL;DR · Principal Applied Research Engineer/Scientist, Siri Labs

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As a Principal Applied Research Engineer at Apple’s Siri Labs, you will lead breakthrough innovation in self-improving systems, agentic memory frameworks, and personalized autonomous multi-agent systems. Your daily work involves advancing intelligent architectures that continuously learn from real-world data, retain contextual knowledge, and coordinate across devices to enhance user experiences. You will collaborate with cross-functional teams to integrate advanced machine learning into scalable product solutions, driving the development of next-generation AI technologies that redefine how users interact with Apple’s ecosystem. This role requires deep expertise in transformer-based large language models (LLMs) and multi-modal foundation models, proficiency in designing AI agents for complex reasoning under hardware constraints, and hands-on experience throughout the model lifecycle from pre-training to deployment.

Skills

Python PyTorch TensorFlow Transformer LLMs Multi-modal_models Cross-modal_attention CI/CD MLOps AWS Azure GCP Docker Kubernetes Git Jupyter Scikit-learn PostgreSQL MongoDB

What you'll do

Advance self-improving systems that learn from real-world data and adapt autonomously.
Design agentic memory frameworks enabling long-term contextual reasoning and personalization.
Architect multi-agent systems for complex problem-solving with coordination and tool use.
Lead rapid prototyping to translate research into validated user experiences and scalable architectures.
Influence platform strategy by partnering cross-functionally to integrate ML systems across platforms.

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 safety alignment.
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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