Applied Machine Learning Engineer - Security
Core
Design and develop ML-enhanced systems to discover, understand, and exploit vulnerabilities across Apple's full-stack platforms (silicon, firmware, kernels, OS) to proactively secure billions of devices.
Role type
Applied Machine Learning Engineer (Offensive Security)
Builds
ML-powered vulnerability detection and analysis tools integrated with fuzzing, static/dynamic analysis, and manual inspection workflows.
Domain
Cybersecurity / Machine Learning / Systems Security
Deliverable
production ML models
Required skills
Large language models, generative modeling, software engineering (C, C++, Python, Swift, Objective-C, Rust), offensive security, analytical problem-solving
Preferred skills
Fuzzing, static analysis, code-analysis tooling, reverse engineering, binary analysis, OS security mitigations
Technologies
Large language models, generative modeling frameworks, C, C++, Python, Swift, Objective-C, Rust
Responsibilities
Integrate with security research teams to analyze complex systems across Apple's full stack; design and develop ML systems that complement traditional analysis methods; leverage raw data and expert behavior to create scalable approaches for identifying subtle weaknesses; collaborate with researchers to validate innovations during real-world security evaluations.
Seniority
Mid-Senior, hands-on IC