Embedded AI Platform Security Engineer

Join our Innovation Team, where we explore cutting-edge concepts at the intersection of Machine Learning and Security. Our mission is to develop forward-looking solutions—such as model protection, privacy-preserving ML, security for agentic AI, and anomaly detection—that will later be integrated into our Edge products. This requires high-level innovation skills combined with a hands-on mindset. If you are passionate about building secure AI systems, exploring new ideas, and turning concepts into prototypes, this role is for you: Design and implement security solutions for customer-provided ML models running on embedded hardware using secure execution environments and enclaves. Responsibilities: Develop secure boot and firmware integrity mechanisms for AI-enabled embedded platforms. Implement runtime hardening and isolation for ML workloads. Enable model protection using Trusted Execution Environments (TEE) and secure enclaves. Ensure secure loading and execution of ML models (ONNX, TensorFlow Lite) on edge devices. Required Skills: Have a background in Computer Science, Cybersecurity, or Cryptography and a strong interest in applied ML, OR Have a background in Machine Learning and an interest in cybersecurity. Embedded programming (C/C++, Rust). Understanding of secure boot, firmware integrity, and runtime security. Experience with or interest in TEEs, TPM integration, and secure enclaves. Familiarity with ML model formats and deployment workflows. Knowledge of cryptographic primitives for integrity and confidentiality. Please note: The successful candidate may/will be responsible for security related tasks. The assignment may/will be in scope of security certifications, therefore a conscious and reliable way of working is necessary. More information about NXP in Austria... #LI-a8a1