Experteer Overview

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In this role you help advance Apple’s security by building AI-enhanced systems that detect and exploit vulnerabilities at scale. You will work closely with security researchers to apply ML across the full stack—from silicon to applications—shaping novel defense techniques. You’ll design multi-step, tool-augmented workflows using LLMs to navigate large codebases and identify subtle weaknesses.

Your work directly supports real-world security evaluations and impactful protection for billions of users. This is a rare chance to combine cutting-edge ML with offensive security in a mission-driven environment.

Compensaciones / Ventajas

- Collaborate with security research teams to understand complex, large-scale systems across the full stack
- Design and develop AI-enhanced systems using LLMs, agentic workflows, and ML approaches
- Supplement traditional analysis methods (fuzzing, static and dynamic analysis, manual inspection) with ML-driven insights
- Leverage raw data and expert behavior to build scalable methods for navigating vast codebases and attack surfaces




- Validate innovations through real-world security evaluations with researchers
- Contribute to the deployment and evaluation of ML models in security contexts
- Collaborate across cross-functional teams to integrate ML solutions into security workflows
- Support scaling of ML models and pipelines for continuous improvement

Responsabilidades

- Experience scaling LLM training and fine-tuning (pretraining, SFT, alignment)
- Strong enthusiasm for security, especially offensive security
- Familiarity with software-analysis techniques (fuzzing, static analysis, code-analysis xugodme tooling, reverse engineering, binary analysis)
- Solid understanding of ML algorithms (supervised, unsupervised, reinforcement learning) and evaluation methods
- Hands-on experience with agentic frameworks (LangChain, LlamaIndex, AutoGen) to build multi-step, tool-augmented workflows
- Familiarity with MLOps (model versioning, CI/CD, experiment tracking tools like MLflow)
- Strong software engineering skills in Python, C, C++, Swift, Objective-C
- Collaborative and effective problem-solving and analytical skills

Requisitos principales

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📌 Applied Machine Learning Engineer - SEAR (Barcelona)
🏢 Apple
📍 Barcelona