Research Scientist, Applied Machine Learning Security (Agent Systems), SEAR

Apple Inc

Quick summary

Work type: On-site
Location: Cupertino, CA
Salary: $181,100–$318,400 / yr
Posted: 56 days ago
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $190k

This role $250k

$118k most similar roles pay here $340k

This role pays more than 84% of similar roles. Most pay $140,000–$239,105 — the shaded band above. At the midpoint, this role pays about $250k versus about $190k 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 · Research Scientist, Applied Machine Learning Security (Agent Systems), SEAR

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As a Staff-Level ML Security Research Scientist at Apple’s SEAR organization, you will join a team dedicated to safeguarding billions of users by integrating cutting-edge machine learning with robust security engineering. Your role involves leading original research on agentic ML systems deployed at scale, identifying real-world vulnerabilities in tool-using models, and designing adversarial evaluations that reflect actual attacker behavior. You will work closely with platform engineering and product security teams to translate your findings into architectural decisions and long-term hardening strategies that reduce risk in production systems. Key skills include a Ph.D. or equivalent experience in machine learning, security, or related fields, along with strong experimental and engineering capabilities focused on reproducibility and operational relevance. Experience with adversarial ML, LLM-based systems, and influencing production through research-driven insights is highly valued.

Skills

Python C++ ML frameworks Adversarial ML Cloud services CI/CD Docker Kubernetes Terraform PostgreSQL Mining and analytics tools Security engineering methodologies LLM-based systems Tool-augmented ML systems

What you'll do

Lead original security research on agentic ML systems deployed at scale.
Design adversarial evaluations reflecting real attacker behavior and system complexity.
Develop mitigations for vulnerabilities that integrate with production requirements.
Define trust boundaries and threat models for agentic ML across Apple platforms.
Influence architectural choices to enhance the security of shipping products.
Bridge research insights into design guidance, test infrastructure, and launch criteria.

What we're looking for

Ph.D. or equivalent experience in machine learning, security, or related field.
Demonstrated applied ML security and adversarial ML experience with real-world impact.
Strong experimental skills and emphasis on reproducibility and operational relevance.
Experience researching or securing large language model (LLM) systems and tool-augmented ML.
Track record of influencing production systems through research-driven insights.
Ability to work fluidly across research, engineering, and security review processes.

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