Applied Machine Learning Engineer - Security
Role details
Job location
Tech stack
Job description
In this role, you will integrate deeply with security research teams to understand the challenges of analyzing large, complex systems across Apple's full stack - from custom silicon and microarchitectural elements to boot ROMs, firmware, kernels, system frameworks, web browser and user applications.
You will design and develop ML-enhanced systems - using large language models, generative modeling, agentic workflows and other approaches - that complement other analysis methods such as fuzzing, static & dynamic analysis, and manual inspection. Your work will leverage raw data and expert behavior to create practical, scalable approaches to help researchers navigate vast codebases, reason about intricate attack surfaces, and identify subtle weaknesses that are challenging to detect manually. You will also collaborate regularly with security researchers to validate and challenge your innovations during real-world security evaluations, ensuring that your work will directly affect meaningful impact.
Requirements
Do you have experience in Python?, Familiarity with software-analysis techniques such as fuzzing, static analysis, code-analysis tooling, reverse engineering, binary-analysis
Familiarity with security mitigations in modern operating systems
Minimum Qualifications Expertise in ML, especially large language models and generative modeling
Experience with and/or strong enthusiasm for security, especially offensive security
Fluency with software engineering using languages such as C, C++, Python, Swift, Objective-C, Rust
Collaborative and effective problem-solving and analytical skills