Experteer Overview In this role you will apply machine learning to fortify Apple's security across its full stack, from silicon to user-facing software.

You will build AI-enhanced systems, including large language model workflows, to help researchers navigate massive codebases and identify subtle vulnerabilities.

You'll collaborate with security researchers to validate innovations during real-world evaluations, delivering measurable security impact at scale.

This is a rare opportunity to combine ML with offensive security to protect billions of users.

Compensaciones / Incentivos • Collaborate with security research teams to understand challenges in analyzing large-scale systems • Design and develop AI-enhanced systems using LLMs and agentic workflows • Implement tool-augmented, multi-step workflows to assist vulnerability discovery • Leverage raw data and expert behavior to build scalable approaches for navigating codebases • Collaborate with researchers to validate innovations during security evaluations • Advance ML approaches that complement fuzzing,



static/dynamic analysis, and manual inspection 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 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 practices (model versioning, CI/CD, experiment tracking tools like MLflow) • Strong software engineering and programming skills in Python, C, C++, Swift, Objective-C • Collaborative and effective problem-solving and analytical skills Requisitos principales •

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