Applied Machine Learning Engineer

Apple Technical Recruitment; Cambridge; On-site; GBP 85,000 - 100,000; Full time

Job summary

Apple seeks an Applied Machine Learning Engineer to help invent and deliver ML-enhanced security methods across the full stack. You will work with security researchers and tool developers to analyze large systems, from silicon to user applications, applying ML techniques to identify weaknesses and improve defenses.

The role focuses on integrating ML with fuzzing, static and dynamic analysis, and cross-domain evaluations to protect billions of devices with Apple’s security teams.

Qualifications

• ML experience with large language models and generative modeling.
• Strong interest in offensive security.
• Proficiency in languages such as C, C++, Python, Swift, Objective-C, or Rust.
• Experience with security analyses such as fuzzing and code-analysis tooling.

Responsibilities

• Collaborate with security researchers to analyze large-scale systems across Apple’s stack.
• Design and develop ML-enhanced security solutions using LLMs and agentic workflows.
• Validate innovations through real-world security evaluations with cross-team collaboration.

Skills

ML Expertise

Security Enthusiasm

C / C++

Python

Swift / Obj-C

Rust

Code Analysis

Fuzzing

Reverse Eng.

Job description

Applied Machine Learning Engineer

Apple's Security Engineering & Architecture organization is responsible for the security of all Apple products. Passionate about safeguarding users, we believe that the best defense requires a great offense. When it comes to securing more than a billion devices running the world's most sophisticated operating systems, that means finding vulnerabilities first.

Our mission is to discover, understand, and exploit vulnerabilities across all layers of Apple’s platforms, and we believe that ML techniques significantly enhance our ability to do so. We are seeking an Applied Machine Learning Engineer who will help us invent and deliver these new methods and techniques.

This position provides rare exposure to a full‑stack view of security along with direct access to expert knowledge, unique datasets, and cross‑domain experience. Your contributions will materially raise the security of products used by billions and strengthen Apple’s ability to defend against adversaries.

Can you make a difference on this scale? Join our extraordinary group of security researchers, tool developers, and machine learning experts, and help protect all Apple users.

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.

• 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
• 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

At Apple, we’re not all the same. And that’s our greatest strength. We draw on the differences in who we are, what we’ve experienced and how we think. Because to create products that serve everyone, we believe in including everyone. Therefore, we are committed to treating all applicants fairly and equally. As a registered Disability Confident employer, we will work with applicants to make any reasonable accommodations. Apple will consider for employment all qualified applicants with criminal backgrounds in a manner consistent with applicable law. Learn more