Applied Machine Learning Engineer - SEAR

Apple; Madrid; Presencial; EUR 70.000 - 100.000; Jornada completa

Descripción de la vacante

Apple’s Security Engineering & Architecture team seeks an Applied Machine Learning Engineer to build AI-enhanced security tools. You will work with researchers and developers to design scalable ML-powered analyses that complement fuzzing, static and dynamic analysis, and manual review.

You will collaborate with security experts to validate innovations in real-world evaluations, shaping methods that help protect billions of users across Apple platforms.

Formación

• Solid understanding of machine learning algorithms, including supervised, unsupervised and reinforcement learning.
• Hands-on experience with agentic frameworks such as LangChain, LlamaIndex, or AutoGen for multi-step, tool-assisted workflows.
• Familiarity with MLOps practices: versioning, CI/CD, experiment tracking (MLflow or similar).
• Strong software engineering skills in Python, C, C++, Swift or Objective-C.
• Collaborative and analytical problem-solving abilities.

Responsabilidades

• Collaborate with security researchers to design AI-enhanced analysis tools.
• Develop and prototypes using large language models and agentic workflows.
• Integrate ML methods with fuzzing, static & dynamic analysis and manual review.
• Validate innovations during real-world security evaluations and projects.

Conocimientos

ML algorithms

Agentic frameworks

MLOps

Programming languages

Collaboration

Descripción del empleo

Summary

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.

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 AI‑enhanced systems using large language models, agentic workflows and machine learning 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.

Minimum Qualifications

• Solid understanding of machine learning algorithms (supervised, unsupervised, and reinforcement learning) and evaluation methods


• Hands‑on experience with agentic frameworks such as LangChain, LlamaIndex, or AutoGen to build multi‑step, tool‑augmented agent workflows


• Familiarity with MLOps practices including model versioning, CI/CD pipelines, and experiment tracking tools such as MLflow or similar


• Strong software engineering and programming skills in languages like Python, C, C++, Swift, Objective‑C


• Collaborative and effective problem‑solving and analytical skills

Preferred Qualifications

• Experience scaling LLM training and fine‑tuning (pretraining, SFT, alignment)


• Strong enthusiasm for security, especially offensive security


• Familiarity with software‑analysis techniques such as fuzzing, static analysis, code‑analysis tooling, reverse engineering, binary‑analysis


• Collaborative and effective problem‑solving and analytical skills

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. We will work with applicants to make any reasonable accommodations.

At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.

Learn about accessibility in Apple’s workplace

Role Number: 200683780-1813