Cyber Security

Position Overview

The AI Security Engineer role is designed for experts with a strong background in AI security engineering, machine learning, and cybersecurity research. The candidate will contribute to securing AI systems—especially in automotive and embedded applications—by leveraging deep technical knowledge of cybersecurity attack vectors and compliance with industry standards.

Key Responsibilities

• Develop, test, and deploy AI-based security solutions for automotive and embedded systems.
• Conduct vulnerability assessments, penetration testing, and red teaming exercises.
• Collaborate with cross-functional teams to ensure adherence to cybersecurity best practices and automotive security standards.
• Continuously research emerging threats and innovate secure AI designs.

Required Qualifications

• Proven experience in AI security engineering, machine learning, or cybersecurity research.
• Deep understanding of cybersecurity attack vectors (e.g., CAN Bus attacks, ECU tampering, replay attacks, brute-force hacks) and the CIA triad.
• Proficiency in Python, TensorFlow, PyTorch, and Scikit-learn for AI model development.
• Hands-on experience with penetration testing, red teaming, or security research.
• Strong knowledge of automotive security standards (e.g., ISO 21434, NHTSA guidelines).
• Experience deploying AI security models on embedded or edge devices.

Preferred Qualifications

• Experience with Linux security hardening (preferably Kali Linux or custom kernels).
• Hands-on expertise in blockchain analytics or AI-driven fraud detection.
• Familiarity with V2X security and encrypted vehicle-to-vehicle (V2V) communications.
• Understanding of homomorphic encryption and federated learning for secure AI training.