CYBER SECURITY SENIOR ENGINEER

You will collaborate with applied researchers, data scientists, and infrastructure teams to design ML security solutions that scale from lab prototypes to enterprise-grade deployments.

• Design, test, and deploy adversarial defenses for ML models across varied deployment architectures (edge, hybrid, cloud)
• Own robustness evaluation pipelines, red-teaming, and model penetration testing
• Develop and maintain tooling for continuous robustness testing and secure MLOps workflows

Master's or PhD in Computer Science, Electrical Engineering, Applied Mathematics, Cybersecurity, or related field. ML / DL Foundations :

Deep understanding of neural networks, optimization, and statistical learning theory. Secure Deployment :

Frameworks & Tools :

Strong skills in

PyTorch

(preferred) or TensorFlow; familiarity with

IBM ART, CleverHans

, or similar security libraries.

Strong communication and cross-functional collaboration skills in English

Publications in top AI and / or security venues (NeurIPS, ICML, AAAI, IEEE S&P, USENIX, ACM CCS, etc.)

is on the forefront of technology innovation, delivering breakthroughs and trusted insights in electronic design, simulation, prototyping, test, manufacturing, and optimization. Our ~15,000 employees create world-class solutions in communications, 5G, automotive, energy, quantum, aerospace, defense, and semiconductor markets for customers in over 100 countries. Our culture embraces a bold vision of where technology can take us and a passion for tackling challenging problems with industry-first solutions. About Keysight AI Labs Keysight's AI Labs is a global R&D group pioneering the integration of into Keysight's test, measurement, and design solutions. Our mission is to transform how engineers design, simulate, and validate advanced systems- from 6G and semiconductors to quantum and automotive-by embedding AI throughout our workflows. As part of this growing team, you will join a vibrant, cross-functional environment that brings together experts in ML engineering, data science, physics-informed modeling, and software development. You'll work closely with domain experts across RF, EM, circuit design, and test & measurement to accelerate scientific innovation through AI.