Applied Machine Learning Engineer - Security

Apple Inc.; Paris; Sur place; EUR 90 000 - 150 000; Plein temps

Résumé du poste

Apple Inc. Security Engineering & Architecture seeks an Applied Machine Learning Engineer to invent and deliver new ML methods for safeguarding Apple products.

You will join a group of security researchers and tool developers tasked with discovering vulnerabilities and strengthening defenses across iOS, macOS, and services. The role combines full-stack security insights with hands-on ML, data-driven experimentation, and collaboration with cross-domain experts to protect billions of users

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.

Connaissances

Machine Learning

Python

C/C++/Swift/Objective-C

LangChain/LlamaIndex/AutoGen

MLOps

Outils

MLflow

Description du poste

Paris, Ile-de-France, France Software and Services

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

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.