The staff-level ML Security Research Scientist role at Apple focuses on applied security research for machine learning systems, particularly those that are agentic and tool-using. The position is part of the Security Engineering & Architecture (SEAR) team, which aims to protect users by integrating security into Apple's products and services. The scientist will lead original research to identify vulnerabilities and drive secure design in production systems. The impact of this role is measured by risk reduction in systems that are deployed at scale.

• Ph.D. or equivalent experience in machine learning, security, systems, or a related field.
• Demonstrated experience in applied ML security, adversarial ML, or systems security with real-world impact.
• Strong experimental and engineering skills, with an emphasis on reproducibility and operational relevance.
• Experience researching or securing LLM-based or tool-augmented ML systems.
• Ability to work fluidly across research, engineering, and security review processes.

• Lead original security research on agentic ML systems deployed at scale.
• Identify real vulnerabilities in tool-using models and design adversarial evaluations.
• Translate research findings into architectural decisions and launch requirements.
• Drive mitigations that integrate into Apple's ML platforms and products.
• Measure impact by risk reduction in production systems.

• Employees at Apple are often offered comprehensive benefits that support physical and mental well-being—flexible medical plans, confidential counseling, onsite wellness centers at major campuses, and resources for fitness and daily life. Families typically receive fertility support, paid parental leave with gradual return, caregiving leave, and dependent-care guidance, while financial perks commonly include stock grants (with purchase discounts), 401(k) matching, and income-protection coverage. Employees also see robust time off, Apple University learning and tuition reimbursement, donation matching and paid volunteer hours, and deep product and partner discounts.