Senior Cyber Security Engineer, hibrido

Keysight Technologies; Madrid; Presencial; EUR 60.000 - 80.000; Jornada completa

Descripción de la vacante

A global technology company in Madrid is seeking a Senior ML Security & Robustness Engineer to lead the design and deployment of secure ML systems. The successful candidate will address adversarial robustness and secure model lifecycle across various deployment targets. A Master’s or PhD in relevant fields is required along with solid skills in PyTorch and TensorFlow. This role offers the opportunity to work in a dynamic team to accelerate scientific innovation through AI.

Formación

• Master’s or PhD in a relevant field.
• Deep understanding of neural networks, optimization, and statistical learning theory.
• Strong skills in PyTorch and familiarity with TensorFlow.

Responsabilidades

• Lead the design and deployment of secure ML systems.
• Design, test, and deploy adversarial defenses for ML models.
• Own robustness evaluation pipelines and model penetration testing.

Conocimientos

Deep understanding of neural networks

Optimization

Statistical learning theory

Strong skills in PyTorch

Strong skills in TensorFlow

Strong communication skills in English

Educación

Master’s or PhD in Computer Science, Electrical Engineering, Applied Mathematics, Cybersecurity

Herramientas

IBM ART

CleverHans

Descripción del empleo

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.

We are seeking a

Senior ML Security & Robustness Engineer

who will lead the design and deployment of secure and resilient ML systems. This is a hands‑on, research‑informed engineering role focused on

adversarial robustness, secure training, and model lifecycle security

across diverse deployment targets, on‑device, hybrid, edge, and cloud.

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.)

Contributions to open‑source ML security projects