Join to apply for the Sr Applied ML Engineer – Physics-Driven Systems & Optimization role at Keysight Technologies Overview Keysight 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. About Keysight AI Labs Keysight’s AI Labs is a integral R&D; group pioneering the integration of machine learning, generative AI 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.
About The Role As a Senior Applied Machine Learning Engineer, you will design, implement, and deploy state‑of‑the‑art ML architectures that merge physics insights, numerical optimization, and modern AI techniques. Graph Neural Networks (GNNs)



for geometry/topology‑aware modeling
Transformers for sequential and multimodal data
Generative Models (GANs, Diffusion) for data augmentation and design candidate generation
Apply advanced optimization and control methods:

Reinforcement Learning (PPO, DDPG, SAC) for continuous tuning and control tasks
Develop scalable training and inference pipelines (multi‑GPU, HPC, AWS) ensuring efficiency and reliability.
Write production‑ready code in Python, C++, and CUDA, integrating with CI/CD pipelines and performance profiling tools.
Benchmark ML and RL models against physics simulators and measurement datasets for robustness and reproducibility.
Collaborate with product teams to embed AI/ML‑based optimization and generative modules into Keysight software.
Master’s or PhD in Applied Mathematics, Scientific Computing, Computer Science, Electrical Engineering, or related field
~Proficiency in Python, C++, CUDA, and GPU performance optimization
~ Experience with multi‑GPU/distributed training in HPC or cloud (Slurm, MPI, AWS)
~ Solid software‑engineering discipline (testing, CI/CD, modular design)
~ Experience applying ML/RL/generative models to parameter tuning, data augmentation, or design exploration
Experience deploying ML/RL systems in production or embedded workflows
Full‑time
Engineering and Information Technology
Appliances, Electrical, and Electronics Manufacturing
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📌 Sr Applied ML Engineer - Physics-Driven Systems & Optimization (Barcelona)
🏢 Keysight Technologies
📍 Barcelona